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REFERENCE page 1
Cut here and keep for reference
ALGEBRA
GEOMETRY
Arithmetic Operations
Geometric Formulas
a
c
ad 1 bc
1 −
b
d
bd
a
b
a
d
ad
− 3 −
c
b
c
bc
d
asb 1 cd − ab 1 ac
a1c
a
c
− 1
b
b
b
Formulas for area A, circumference C, and volume V:
Triangle
Circle
A − 12 bh
Sector of Circle
A − !r
− 12 ab sin "
A − 12 r 2"
2
s − r" s" in radiansd
C − 2!r
Exponents and Radicals
sx mdn − x m n
SD
−
Î
s xy − s x s y
n
n
r
h
¨
r
xn
yn
r
Sphere
m
Cylinder
V − 43 !r 3
n
x
s
x
− n
y
y
s
s
¨
b
n m
n
x myn − s
x − (s
x)
n
x 1yn − s
x
n
n
x
y
sxydn − x n y n
n
a
xm
− x m2n
xn
1
x2n − n
x
x m x n − x m1n
Cone
V − 13 !r 2h
2
V − !r h
A − 4!r 2
A − ! rsr 2 1 h 2
U
Factoring Special Polynomials
U
x 2 2 y 2 − sx 1 ydsx 2 yd
x 3 1 y 3 − sx 1 ydsx 2 2 xy 1 y 2d
r
x 3 2 y 3 − sx 2 ydsx 2 1 xy 1 y 2d
Binomial Theorem
Distance and Midpoint Formulas
sx 1 yd − x 1 2xy 1 y
2
2
sx 2 yd − x 2 2xy 1 y
2
2
2
2
Distance between P1sx1, y1d and P2sx 2, y2d:
sx 1 yd3 − x 3 1 3x 2 y 1 3xy 2 1 y 3
d − ssx 2 2 x1d2 1 s y2 2 y1d2
sx 2 yd3 − x 3 2 3x 2 y 1 3xy 2 2 y 3
sx 1 ydn − x n 1 nx n21y 1
where
SD
n
k
nsn 2 1d n22 2
x y
2
SD
n n2k k …
x y 1
1 nxy n21 1 y n
k
nsn 2 1d … sn 2 k 1 1d
−
1?2?3?…?k
1…1
Midpoint of P1 P2:
2b 6 sb 2 2 4ac
If ax 2 1 bx 1 c − 0, then x −
.
2a
x1 1 x 2 y1 1 y2
,
2
2
D
Slope of line through P1sx1, y1d and P2sx 2, y2d:
m−
y2 2 y1
x 2 2 x1
Point-slope equation of line through P1sx1, y1d with slope m:
Inequalities and Absolute Value
y 2 y1 − msx 2 x1d
If a , b and b , c, then a , c.
If a , b, then a 1 c , b 1 c.
S
Lines
Quadratic Formula
Slope-intercept equation of line with slope m and y-intercept b:
If a , b and c . 0, then ca , cb.
y − mx 1 b
If a , b and c , 0, then ca . cb.
Circles
If a . 0, then
| |
| x | , a means 2a , x , a
| x | . a means x . a or x , 2a
x −a
means
x−a
K
K
or
x − 2a
Equation of the circle with center sh, kd and radius r:
sx 2 hd2 1 s y 2 kd2 − r 2
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
REFERENCE page 2
TRIGONOMETRY
Angle Measurement
Fundamental Identities
csc " −
1
sin "
sec " −
1
cos "
tan " −
sin "
cos "
cot " −
cos "
sin "
s" in radiansd
cot " −
1
tan "
sin2 " 1 cos2 " − 1
Right Angle Trigonometry
1 1 tan2 " − sec 2 "
1 1 cot 2 " − csc 2 "
sins2"d − 2sin "
coss2"d − cos "
tans2"d − 2tan "
sin
! radians − 1808
18 −
!
rad
180
1 rad −
r
180°
!
¨
r
s − r"
opp
hyp
csc " −
cos " −
adj
hyp
sec " −
hyp
adj
tan " −
opp
adj
cot " −
adj
opp
sin " −
s
hyp
opp
hyp
opp
¨
adj
cos
Trigonometric Functions
sin " −
y
r
csc " −
x
cos " −
r
y
tan " −
x
r
y
S D
!
2 " − sin "
2
S D
S D
tan
!
2 " − cos "
2
!
2 " − cot "
2
The Law of Sines
y
r
sec " −
x
x
cot " −
y
r
B
sin A
sin B
sin C
−
−
a
b
c
(x, y)
a
¨
The Law of Cosines
x
b
a 2 − b 2 1 c 2 2 2bc cos A
Graphs of Trigonometric Functions
y
1
b 2 − a 2 1 c 2 2 2ac cos B
y
y=sin x
C
c
y
y=tan x
c 2 − a 2 1 b 2 2 2ab cos C
A
y=cos x
π
1
2π
Addition and Subtraction Formulas
2π
π
x
_1
_1
2π x
x
π
sinsx 1 yd − sin x cos y 1 cos x sin y
sinsx 2 yd − sin x cos y 2 cos x sin y
cossx 1 yd − cos x cos y 2 sin x sin y
y
y=csc x
y
y
y=cot x
cossx 2 yd − cos x cos y 1 sin x sin y
1
1
_1
y=sec x
π
2π x
π
_1
2π x
π
2π x
tansx 1 yd −
tan x 1 tan y
1 2 tan x tan y
tansx 2 yd −
tan x 2 tan y
1 1 tan x tan y
Double-Angle Formulas
sin 2x − 2 sin x cos x
Trigonometric Functions of Important Angles
"
08
radians
sin "
cos "
tan "
0
0
1
0
308
!y6
1y2
s3y3
!y4
s2y2
s3y2
458
608
!y3
s3y2
908
!y2
1
s2y2
1
1y2
s3
0
—
cos 2x − cos 2x 2 sin 2x − 2 cos 2x 2 1 − 1 2 2 sin 2x
tan 2x −
2 tan x
1 2 tan2x
Half-Angle Formulas
sin 2x −
1 2 cos 2x
2
cos 2x −
1 1 cos 2x
2
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CALCULUS
EAR LY TR ANS CENDENTA LS
NINTH EDITION
JAMES STEWART
McMASTER UNIVERSITY
AND
UNIVERSITY OF TORONTO
DANIEL CLEGG
PALOMAR COLLEGE
SALEEM WATSON
CALIFORNIA STATE UNIVERSITY, LONG BEACH
Australia • Brazil • Mexico • Singapore • United Kingdom • United States
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formats, please visit www.cengage.com/highered to search by ISBN#, author, title, or keyword for
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Important Notice: Media content referenced within the product description or the product
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Calculus: Early Transcendentals, Ninth Edition
James Stewart, Daniel Clegg, Saleem Watson
© 2021, 2016 Cengage Learning, Inc.
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Cengage
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your online learning solution, or purchase materials for your course, visit
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Printed in the United States of America
Print Number: 01
Print Year: 2019
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Contents
Preface x
A Tribute to James Stewart
About the Authors
xxii
xxiii
Technology in the Ninth Edition
To the Student
xxv
Diagnostic Tests
xxvi
xxiv
A Preview of Calculus 1
1 Functions and Models
1.1
1.2
1.3
1.4
1.5
7
Four Ways to Represent a Function 8
Mathematical Models: A Catalog of Essential Functions 21
New Functions from Old Functions 36
Exponential Functions 45
Inverse Functions and Logarithms 54
Review 67
Principles of Problem Solving 70
2 Limits and Derivatives
2.1
2.2
2.3
2.4
2.5
2.6
2.7
77
The Tangent and Velocity Problems 78
The Limit of a Function 83
Calculating Limits Using the Limit Laws 94
The Precise Definition of a Limit 105
Continuity 115
Limits at Infinity; Horizontal Asymptotes 127
Derivatives and Rates of Change 140
WR ITIN G PROJ EC T
• Early Methods for Finding Tangents 152
2.8 The Derivative as a Function 153
Review
166
Problems Plus 171
iii
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
iv
CONTENTS
3
Differentiation Rules
173
3.1 Derivatives of Polynomials and Exponential Functions 174
APPLIED PROJ EC T
• Building a Better Roller Coaster 184
3.2 The Product and Quotient Rules 185
3.3 Derivatives of Trigonometric Functions 191
3.4 The Chain Rule 199
APPLIED PROJ EC T
• Where Should a Pilot Start Descent? 209
3.5 Implicit Differentiation 209
D IS COV ERY PROJ EC T
• Families of Implicit Curves 217
3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions 217
3.7 Rates of Change in the Natural and Social Sciences 225
3.8 Exponential Growth and Decay 239
APPLIED PROJ EC T
• Controlling Red Blood Cell Loss During Surgery 247
3.9 Related Rates 247
3.10 Linear Approximations and Differentials 254
D IS COV ERY PROJ EC T
• Polynomial Approximations 260
3.11 Hyperbolic Functions 261
Review
269
Problems Plus 274
4
Applications of Differentiation
279
4.1 Maximum and Minimum Values 280
APPLIED PROJ EC T
• The Calculus of Rainbows 289
4.2 The Mean Value Theorem 290
4.3 What Derivatives Tell Us about the Shape of a Graph 296
4.4 Indeterminate Forms and l’Hospital’s Rule 309
WR IT IN G PROJ EC T
• The Origins of l’Hospital’s Rule 319
4.5 Summary of Curve Sketching 320
4.6 Graphing with Calculus and Technology 329
4.7 Optimization Problems 336
APPLIED PROJ EC T
• The Shape of a Can 349
APPLIED PROJ EC T
• Planes and Birds: Minimizing Energy
350
4.8 Newton’s Method 351
4.9 Antiderivatives 356
Review
364
Problems Plus 369
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
v
CONTENTS
5
Integrals
371
5.1 The Area and Distance Problems 372
5.2 The Definite Integral 384
D IS COV ERY PROJ EC T
• Area Functions 398
5.3 The Fundamental Theorem of Calculus 399
5.4 Indefinite Integrals and the Net Change Theorem 409
WR ITIN G PROJ EC T
• Newton, Leibniz, and the Invention of Calculus 418
5.5 The Substitution Rule 419
Review
428
Problems Plus 432
6
Applications of Integration
435
6.1 Areas Between Curves 436
APPLIED PROJ EC T
6.2
6.3
6.4
6.5
• The Gini Index 445
Volumes 446
Volumes by Cylindrical Shells 460
Work 467
Average Value of a Function 473
APPLIED PROJ EC T
• Calculus and Baseball 476
APPLIED PROJ EC T
• Where to Sit at the Movies 478
Review
478
Problems Plus 481
7
Techniques of Integration
7.1
7.2
7.3
7.4
7.5
7.6
Integration by Parts 486
Trigonometric Integrals 493
Trigonometric Substitution 500
Integration of Rational Functions by Partial Fractions 507
Strategy for Integration 517
Integration Using Tables and Technology 523
D IS COV ERY PROJ EC T
• Patterns in Integrals 528
7.7 Approximate Integration 529
7.8 Improper Integrals 542
Review
552
Problems Plus 556
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
485
vi
CONTENTS
8
Further Applications of Integration
559
8.1 Arc Length 560
D IS COV ERY PROJ EC T
• Arc Length Contest 567
8.2 Area of a Surface of Revolution 567
D IS COV ERY PROJ EC T
• Rotating on a Slant 575
8.3 Applications to Physics and Engineering 576
D IS COV ERY PROJ EC T
• Complementary Coffee Cups 587
8.4 Applications to Economics and Biology 587
8.5 Probability 592
Review
600
Problems Plus 602
9
Differential Equations
605
9.1 Modeling with Differential Equations 606
9.2 Direction Fields and Euler’s Method 612
9.3 Separable Equations 621
APPLIED PROJ EC T
• How Fast Does a Tank Drain? 630
9.4 Models for Population Growth 631
9.5 Linear Equations 641
APPLIED PROJ EC T
• Which Is Faster, Going Up or Coming Down? 648
9.6 Predator-Prey Systems 649
Review
656
Problems Plus 659
10 Parametric Equations and Polar Coordinates
10.1
Curves Defined by Parametric Equations 662
D IS COV ERY PROJ EC T
• Running Circles Around Circles 672
10.2
Calculus with Parametric Curves
10.3
Polar Coordinates 684
D IS COV ERY PROJ EC T
D IS COV ERY PROJ EC T
10.4
10.5
661
673
• Bézier Curves 684
• Families of Polar Curves 694
Calculus in Polar Coordinates
694
Conic Sections 702
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CONTENTS
10.6
vii
Conic Sections in Polar Coordinates 711
Review
719
Problems Plus 722
11 Sequences, Series, and Power Series
11.1
Sequences 724
D IS COV ERY PROJ EC T
11.2
11.3
11.4
11.5
11.6
11.7
11.8
11.9
11.10
723
Series
• Logistic Sequences 738
738
The Integral Test and Estimates of Sums 751
The Comparison Tests 760
Alternating Series and Absolute Convergence 765
The Ratio and Root Tests 774
Strategy for Testing Series 779
Power Series 781
Representations of Functions as Power Series 787
Taylor and Maclaurin Series 795
D IS COV ERY PROJ EC T
WR ITIN G PROJ EC T
• An Elusive Limit 810
• How Newton Discovered the Binomial Series 811
11.11 Applications of Taylor Polynomials 811
APPLIED PROJ EC T
Review
• Radiation from the Stars 820
821
Problems Plus 825
12 Vectors and the Geometry of Space
12.1
12.2
Three-Dimensional Coordinate Systems 830
Vectors 836
D IS COV ERY PROJ EC T
12.3
12.4
• The Shape of a Hanging Chain 846
The Dot Product 847
The Cross Product 855
D IS COV ERY PROJ EC T
• The Geometry of a Tetrahedron 864
12.5
Equations of Lines and Planes 864
12.6
Cylinders and Quadric Surfaces 875
Review 883
D IS COV ERY PROJ EC T
• Putting 3D in Perspective 874
Problems Plus 887
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
829
viii
CONTENTS
13 Vector Functions
13.1
13.2
13.3
13.4
889
Vector Functions and Space Curves 890
Derivatives and Integrals of Vector Functions 898
Arc Length and Curvature 904
Motion in Space: Velocity and Acceleration 916
APPLIED PROJ EC T
Review
• Kepler’s Laws 925
927
Problems Plus 930
14 Partial Derivatives
14.1
14.2
14.3
Functions of Several Variables 934
Limits and Continuity 951
Partial Derivatives 961
D IS COV ERY PROJ EC T
14.4
974
• The Speedo LZR Racer 984
The Chain Rule 985
Directional Derivatives and the Gradient Vector 994
Maximum and Minimum Values 1008
D IS COV ERY PROJ EC T
14.8
• Deriving the Cobb-Douglas Production Function 973
Tangent Planes and Linear Approximations
APPLIED PROJ EC T
14.5
14.6
14.7
933
• Quadratic Approximations and Critical Points 1019
Lagrange Multipliers 1020
APPLIED PROJ EC T
• Rocket Science 1028
APPLIED PROJ EC T
• Hydro-Turbine Optimization 1030
Review
1031
Problems Plus 1035
15 Multiple Integrals
15.1
15.2
15.3
15.4
15.5
15.6
Double Integrals over Rectangles 1038
Double Integrals over General Regions 1051
Double Integrals in Polar Coordinates 1062
Applications of Double Integrals 1069
Surface Area 1079
Triple Integrals 1082
D IS COV ERY PROJ EC T
15.7
1037
• Volumes of Hyperspheres 1095
Triple Integrals in Cylindrical Coordinates 1095
D IS COV ERY PROJ EC T
• The Intersection of Three Cylinders
1101
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
ix
CONTENTS
15.8
Triple Integrals in Spherical Coordinates 1102
15.9
Change of Variables in Multiple Integrals 1109
APPLIED PROJ EC T
Review
• Roller Derby 1108
1117
Problems Plus 1121
16 Vector Calculus
16.1
16.2
16.3
16.4
16.5
16.6
16.7
16.8
16.9
16.10
Vector Fields
1123
1124
Line Integrals 1131
The Fundamental Theorem for Line Integrals 1144
Green’s Theorem 1154
Curl and Divergence 1161
Parametric Surfaces and Their Areas 1170
Surface Integrals 1182
Stokes’ Theorem 1195
The Divergence Theorem 1201
Summary 1208
Review 1209
Problems Plus 1213
Appendixes
A
B
C
D
E
F
G
H
Numbers, Inequalities, and Absolute Values A2
Coordinate Geometry and Lines A10
Graphs of Second-Degree Equations A16
Trigonometry A24
Sigma Notation A36
Proofs of Theorems A41
The Logarithm Defined as an Integral A53
Answers to Odd-Numbered Exercises A61
Index A143
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
A1
Preface
A great discovery solves a great problem but there is a grain of discovery in the solution
of any problem. Your problem may be modest; but if it challenges your curiosity and
brings into play your inventive faculties, and if you solve it by your own means, you may
experience the tension and enjoy the triumph of discovery.
george polya
The art of teaching, Mark Van Doren said, is the art of assisting discovery. In this Ninth
Edition, as in all of the preceding editions, we continue the tradition of writing a book
that, we hope, assists students in discovering calculus — both for its practical power and
its surprising beauty. We aim to convey to the student a sense of the utility of calculus as
well as to promote development of technical ability. At the same time, we strive to give
some appreciation for the intrinsic beauty of the subject. Newton undoubtedly experienced a sense of triumph when he made his great discoveries. We want students to share
some of that excitement.
The emphasis is on understanding concepts. Nearly all calculus instructors agree that
conceptual understanding should be the ultimate goal of calculus instruction; to implement this goal we present fundamental topics graphically, numerically, algebraically,
and verbally, with an emphasis on the relationships between these different representations. Visualization, numerical and graphical experimentation, and verbal descriptions
can greatly facilitate conceptual understanding. Moreover, conceptual understanding
and technical skill can go hand in hand, each reinforcing the other.
We are keenly aware that good teaching comes in different forms and that there
are different approaches to teaching and learning calculus, so the exposition and exercises are designed to accommodate different teaching and learning styles. The features
(including projects, extended exercises, principles of problem solving, and historical
insights) provide a variety of enhancements to a central core of fundamental concepts
and skills. Our aim is to provide instructors and their students with the tools they need
to chart their own paths to discovering calculus.
Alternate Versions
The Stewart Calculus series includes several other calculus textbooks that might be
preferable for some instructors. Most of them also come in single variable and multivariable versions.
• Calculus, Ninth Edition, is similar to the present textbook except that the exponential, logarithmic, and inverse trigonometric functions are covered after the chapter
on integration.
• Essential Calculus, Second Edition, is a much briefer book (840 pages), though it
contains almost all of the topics in Calculus, Ninth Edition. The relative brevity is
achieved through briefer exposition of some topics and putting some features on the
website.
x
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
PREFACE
xi
• Essential Calculus: Early Transcendentals, Second Edition, resembles Essential
Calculus, but the exponential, logarithmic, and inverse trigonometric functions are
covered in Chapter 3.
• Calculus: Concepts and Contexts, Fourth Edition, emphasizes conceptual understanding even more strongly than this book. The coverage of topics is not encyclopedic and the material on transcendental functions and on parametric equations is
woven throughout the book instead of being treated in separate chapters.
• Brief Applied Calculus is intended for students in business, the social sciences, and
the life sciences.
• Biocalculus: Calculus for the Life Sciences is intended to show students in the life
sciences how calculus relates to biology.
• Biocalculus: Calculus, Probability, and Statistics for the Life Sciences contains all
the content of Biocalculus: Calculus for the Life Sciences as well as three additional chapters covering probability and statistics.
What’s New in the Ninth Edition?
The overall structure of the text remains largely the same, but we have made many
improvements that are intended to make the Ninth Edition even more usable as a teaching tool for instructors and as a learning tool for students. The changes are a result of
conversations with our colleagues and students, suggestions from users and reviewers,
insights gained from our own experiences teaching from the book, and from the copious
notes that James Stewart entrusted to us about changes that he wanted us to consider for
the new edition. In all the changes, both small and large, we have retained the features
and tone that have contributed to the success of this book.
• More than 20% of the exercises are new:
Basic exercises have been added, where appropriate, near the beginning of exercise sets. These exercises are intended to build student confidence and reinforce
understanding of the fundamental concepts of a section. (See, for instance, Exercises 7.3.1 – 4, 9.1.1 – 5, 11.4.3 – 6.)
Some new exercises include graphs intended to encourage students to understand
how a graph facilitates the solution of a problem; these exercises complement
subsequent exercises in which students need to supply their own graph. (See
Exercises 6.2.1– 4, Exercises 10.4.43 – 46 as well as 53 – 54, 15.5.1 – 2, 15.6.9 – 12,
16.7.15 and 24, 16.8.9 and 13.)
Some exercises have been structured in two stages, where part (a) asks for the
setup and part (b) is the evaluation. This allows students to check their answer
to part (a) before completing the problem. (See Exercises 6.1.1 – 4, 6.3.3 – 4,
15.2.7 – 10.)
Some challenging and extended exercises have been added toward the end of
selected exercise sets (such as Exercises 6.2.87, 9.3.56, 11.2.79 – 81, and 11.9.47).
Titles have been added to selected exercises when the exercise extends a concept discussed in the section. (See, for example, Exercises 2.6.66, 10.1.55 – 57,
15.2.80 – 81.)
Some of our favorite new exercises are 1.3.71, 3.4.99, 3.5.65, 4.5.55 – 58, 6.2.79,
6.5.18, 10.5.69, 15.1.38, and 15.4.3 – 4. In addition, Problem 14 in the Problems
Plus following Chapter 6 and Problem 4 in the Problems Plus following Chapter 15 are interesting and challenging.
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xii
PREFACE
• New examples have been added, and additional steps have been added to the solutions of some existing examples. (See, for instance, Example 2.7.5, Example 6.3.5,
Example 10.1.5, Examples 14.8.1 and 14.8.4, and Example 16.3.4.)
• Several sections have been restructured and new subheads added to focus the
organization around key concepts. (Good illustrations of this are Sections 2.3, 11.1,
11.2, and 14.2.)
• Many new graphs and illustrations have been added, and existing ones updated, to
provide additional graphical insights into key concepts.
• A few new topics have been added and others expanded (within a section or
in extended exercises) that were requested by reviewers. (Examples include a
subsection on torsion in Section 13.3, symmetric difference quotients in Exercise 2.7.60, and improper integrals of more than one type in Exercises 7.8.65 – 68.)
• New projects have been added and some existing projects have been updated.
(For instance, see the Discovery Project following Section 12.2, The Shape of a
Hanging Chain.)
• Derivatives of logarithmic functions and inverse trigonometric functions are now
covered in one section (3.6) that emphasizes the concept of the derivative of an
inverse function.
• Alternating series and absolute convergence are now covered in one section (11.5).
• The chapter on Second-Order Differential Equations, as well as the associated
appendix section on complex numbers, has been moved to the website.
Features
Each feature is designed to complement different teaching and learning practices.
Throughout the text there are historical insights, extended exercises, projects, problemsolving principles, and many opportunities to experiment with concepts by using technology. We are mindful that there is rarely enough time in a semester to utilize all of
these features, but their availability in the book gives the instructor the option to assign
some and perhaps simply draw attention to others in order to emphasize the rich ideas
of calculus and its crucial importance in the real world.
n Conceptual Exercises
The most important way to foster conceptual understanding is through the problems that
the instructor assigns. To that end we have included various types of problems. Some
exercise sets begin with requests to explain the meanings of the basic concepts of the
section (see, for instance, the first few exercises in Sections 2.2, 2.5, 11.2, 14.2, and
14.3) and most exercise sets contain exercises designed to reinforce basic understanding
(such as Exercises 2.5.3 – 10, 5.5.1 – 8, 6.1.1 – 4, 7.3.1 – 4, 9.1.1 – 5, and 11.4.3 – 6). Other
exercises test conceptual understanding through graphs or tables (see Exercises 2.7.17,
2.8.36 – 38, 2.8.47 – 52, 9.1.23 – 25, 10.1.30 – 33, 13.2.1 – 2, 13.3.37 – 43, 14.1.41 – 44,
14.3.2, 14.3.4 – 6, 14.6.1 – 2, 14.7.3 – 4, 15.1.6 – 8, 16.1.13 – 22, 16.2.19 – 20, and 16.3.1 – 2).
Many exercises provide a graph to aid in visualization (see for instance Exercises 6.2.1 – 4, 10.4.43 – 46, 15.5.1 – 2, 15.6.9 – 12, and 16.7.24). Another type of exercise
uses verbal descriptions to gauge conceptual understanding (see Exercises 2.5.12,
2.8.66, 4.3.79 – 80, and 7.8.79). In addition, all the review sections begin with a Concept
Check and a True-False Quiz.
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PREFACE
xiii
We particularly value problems that combine and compare graphical, numerical, and
algebraic approaches (see Exercises 2.6.45 – 46, 3.7.29, and 9.4.4).
n Graded Exercise Sets
Each exercise set is carefully graded, progressing from basic conceptual exercises, to
skill-development and graphical exercises, and then to more challenging exercises that
often extend the concepts of the section, draw on concepts from previous sections, or
involve applications or proofs.
n Real-World Data
Real-world data provide a tangible way to introduce, motivate, or illustrate the concepts
of calculus. As a result, many of the examples and exercises deal with functions defined
by such numerical data or graphs. These real-world data have been obtained by contacting companies and government agencies as well as researching on the Internet and in
libraries. See, for instance, Figure 1 in Section 1.1 (seismograms from the Northridge
earthquake), Exercise 2.8.36 (number of cosmetic surgeries), Exercise 5.1.12 (velocity
of the space shuttle Endeavour), Exercise 5.4.83 (power consumption in the New England states), Example 3 in Section 14.4 (the heat index), Figure 1 in Section 14.6 (temperature contour map), Example 9 in Section 15.1 (snowfall in Colorado), and Figure 1
in Section 16.1 (velocity vector fields of wind in San Francisco Bay).
n Projects
One way of involving students and making them active learners is to have them work
(perhaps in groups) on extended projects that give a feeling of substantial accomplishment when completed. There are three kinds of projects in the text.
Applied Projects involve applications that are designed to appeal to the imagination of students. The project after Section 9.5 asks whether a ball thrown upward takes
longer to reach its maximum height or to fall back to its original height (the answer
might surprise you). The project after Section 14.8 uses Lagrange multipliers to determine the masses of the three stages of a rocket so as to minimize the total mass while
enabling the rocket to reach a desired velocity.
Discovery Projects anticipate results to be discussed later or encourage discovery
through pattern recognition (see the project following Section 7.6, which explores patterns in integrals). Other discovery projects explore aspects of geometry: tetrahedra
(after Section 12.4), hyperspheres (after Section 15.6), and intersections of three cylinders (after Section 15.7). Additionally, the project following Section 12.2 uses the
geometric definition of the derivative to find a formula for the shape of a hanging chain.
Some projects make substantial use of technology; the one following Section 10.2
shows how to use Bézier curves to design shapes that represent letters for a laser printer.
Writing Projects ask students to compare present-day methods with those of the
founders of calculus — Fermat’s method for finding tangents, for instance, following
Section 2.7. Suggested references are supplied.
More projects can be found in the Instructor’s Guide. There are also extended exercises that can serve as smaller projects. (See Exercise 4.7.53 on the geometry of beehive
cells, Exercise 6.2.87 on scaling solids of revolution, or Exercise 9.3.56 on the formation of sea ice.)
n Problem Solving
Students usually have difficulties with problems that have no single well-defined
procedure for obtaining the answer. As a student of George Polya, James Stewart
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xiv
PREFACE
experienced first-hand Polya’s delightful and penetrating insights into the process
of problem solving. Accordingly, a modified version of Polya’s four-stage problemsolving strategy is presented following Chapter 1 in Principles of Problem Solving.
These principles are applied, both explicitly and implicitly, throughout the book. Each of
the other chapters is followed by a section called Problems Plus, which features examples
of how to tackle challenging calculus problems. In selecting the Problems Plus problems we have kept in mind the following advice from David Hilbert: “A mathematical
problem should be difficult in order to entice us, yet not inaccessible lest it mock our
efforts.” We have used these problems to great effect in our own calculus classes; it is
gratifying to see how students respond to a challenge. James Stewart said, “When I put
these challenging problems on assignments and tests I grade them in a different way . . .
I reward a student significantly for ideas toward a solution and for recognizing which
problem-solving principles are relevant.”
n Technology
When using technology, it is particularly important to clearly understand the concepts that underlie the images on the screen or the results of a calculation. When
properly used, graphing calculators and computers are powerful tools for discovering
and understanding those concepts. This textbook can be used either with or without
technology — we use two special symbols to indicate clearly when a particular type of
assistance from technology is required. The icon ; indicates an exercise that definitely
requires the use of graphing software or a graphing calculator to aid in sketching a
graph. (That is not to say that the technology can’t be used on the other exercises as
well.) The symbol
means that the assistance of software or a graphing calculator is
needed beyond just graphing to complete the exercise. Freely available websites such
as WolframAlpha.com or Symbolab.com are often suitable. In cases where the full
resources of a computer algebra system, such as Maple or Mathematica, are needed, we
state this in the exercise. Of course, technology doesn’t make pencil and paper obsolete.
Hand calculation and sketches are often preferable to technology for illustrating and
reinforcing some concepts. Both instructors and students need to develop the ability
to decide where using technology is appropriate and where more insight is gained by
working out an exercise by hand.
n WebAssign: webassign.net
This Ninth Edition is available with WebAssign, a fully customizable online solution
for STEM disciplines from Cengage. WebAssign includes homework, an interactive
mobile eBook, videos, tutorials and Explore It interactive learning modules. Instructors
can decide what type of help students can access, and when, while working on assignments. The patented grading engine provides unparalleled answer evaluation, giving
students instant feedback, and insightful analytics highlight exactly where students are
struggling. For more information, visit cengage.com/WebAssign.
n Stewart Website
Visit StewartCalculus.com for these additional materials:
• Homework Hints
• Solutions to the Concept Checks (from the review section of each chapter)
• Algebra and Analytic Geometry Review
• Lies My Calculator and Computer Told Me
• History of Mathematics, with links to recommended historical websites
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
PREFACE
xv
• Additional Topics (complete with exercise sets): Fourier Series, Rotation of Axes,
Formulas for the Remainder Theorem in Taylor Series
• Additional chapter on second-order differential equations, including the method of
series solutions, and an appendix section reviewing complex numbers and complex
exponential functions
• Instructor Area that includes archived problems (drill exercises that appeared in
previous editions, together with their solutions)
• Challenge Problems (some from the Problems Plus sections from prior editions)
• Links, for particular topics, to outside Web resources
Content
Diagnostic Tests
The book begins with four diagnostic tests, in Basic Algebra, Analytic Geometry, Functions, and Trigonometry.
A Preview of Calculus
This is an overview of the subject and includes a list of questions to motivate the study
of calculus.
Functions and Models
From the beginning, multiple representations of functions are stressed: verbal, numerical, visual, and algebraic. A discussion of mathematical models leads to a review of the
standard functions, including exponential and logarithmic functions, from these four
points of view.
2 Limits and Derivatives
The material on limits is motivated by a prior discussion of the tangent and velocity problems. Limits are treated from descriptive, graphical, numerical, and algebraic
points of view. Section 2.4, on the precise definition of a limit, is an optional section.
Sections 2.7 and 2.8 deal with derivatives (including derivatives for functions defined
graphically and numerically) before the differentiation rules are covered in Chapter 3.
Here the examples and exercises explore the meaning of derivatives in various contexts.
Higher derivatives are introduced in Section 2.8.
3
Differentiation Rules
All the basic functions, including exponential, logarithmic, and inverse trigonometric
functions, are differentiated here. The latter two classes of functions are now covered in
one section that focuses on the derivative of an inverse function. When derivatives are
computed in applied situations, students are asked to explain their meanings. Exponential growth and decay are included in this chapter.
4 Applications of Differentiation
The basic facts concerning extreme values and shapes of curves are deduced from the
Mean Value Theorem. Graphing with technology emphasizes the interaction between
calculus and machines and the analysis of families of curves. Some substantial optimization problems are provided, including an explanation of why you need to raise your
head 42° to see the top of a rainbow.
1
Integrals
The area problem and the distance problem serve to motivate the definite integral, with
sigma notation introduced as needed. (Full coverage of sigma notation is provided in
Appendix E.) Emphasis is placed on explaining the meanings of integrals in various
contexts and on estimating their values from graphs and tables.
Applications of Integration
This chapter presents the applications of integration — area, volume, work, average
value — that can reasonably be done without specialized techniques of integration.
General methods are emphasized. The goal is for students to be able to divide a quantity
into small pieces, estimate with Riemann sums, and recognize the limit as an integral.
5
6
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xvi
PREFACE
7 Techniques of Integration
8
All the standard methods are covered but, of course, the real challenge is to be able to
recognize which technique is best used in a given situation. Accordingly, a strategy for
evaluating integrals is explained in Section 7.5. The use of mathematical software is
discussed in Section 7.6.
Further Applications of Integration This chapter contains the applications of integration — arc length and surface area — for
which it is useful to have available all the techniques of integration, as well as applications to biology, economics, and physics (hydrostatic force and centers of mass). A section on probability is included. There are more applications here than can realistically be
covered in a given course. Instructors may select applications suitable for their students
and for which they themselves have enthusiasm.
Differential Equations
Modeling is the theme that unifies this introductory treatment of differential equations.
Direction fields and Euler’s method are studied before separable and linear equations
are solved explicitly, so that qualitative, numerical, and analytic approaches are given
equal consideration. These methods are applied to the exponential, logistic, and other
models for population growth. The first four or five sections of this chapter serve as a
good introduction to first-order differential equations. An optional final section uses
predator-prey models to illustrate systems of differential equations.
Parametric Equations and
Polar Coordinates
This chapter introduces parametric and polar curves and applies the methods of calculus to them. Parametric curves are well suited to projects that require graphing with
technology; the two presented here involve families of curves and Bézier curves. A brief
treatment of conic sections in polar coordinates prepares the way for Kepler’s Laws in
Chapter 13.
Sequences, Series, and Power
Series
The convergence tests have intuitive justifications (see Section 11.3) as well as formal
proofs. Numerical estimates of sums of series are based on which test was used to prove
convergence. The emphasis is on Taylor series and polynomials and their applications
to physics.
12 Vectors and the Geometry
of Space
The material on three-dimensional analytic geometry and vectors is covered in this and
the next chapter. Here we deal with vectors, the dot and cross products, lines, planes,
and surfaces.
13 Vector Functions
This chapter covers vector-valued functions, their derivatives and integrals, the length
and curvature of space curves, and velocity and acceleration along space curves, culminating in Kepler’s laws.
14
Partial Derivatives
Functions of two or more variables are studied from verbal, numerical, visual, and algebraic points of view. In particular, partial derivatives are introduced by looking at a
specific column in a table of values of the heat index (perceived air temperature) as a
function of the actual temperature and the relative humidity.
15
Multiple Integrals
Contour maps and the Midpoint Rule are used to estimate the average snowfall and
average temperature in given regions. Double and triple integrals are used to compute
volumes, surface areas, and (in projects) volumes of hyperspheres and volumes of intersections of three cylinders. Cylindrical and spherical coordinates are introduced in the
context of evaluating triple integrals. Several applications are considered, including
computing mass, charge, and probabilities.
16 Vector Calculus
Vector fields are introduced through pictures of velocity fields showing San Francisco
Bay wind patterns. The similarities among the Fundamental Theorem for line integrals,
Green’s Theorem, Stokes’ Theorem, and the Divergence Theorem are emphasized.
9
10
11
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PREFACE
17
Second-Order Differential
Equations
xvii
Since first-order differential equations are covered in Chapter 9, this online chapter deals
with second-order linear differential equations, their application to vibrating springs and
electric circuits, and series solutions.
Ancillaries
Calculus, Early Transcendentals, Ninth Edition, is supported by a complete set of ancillaries. Each piece has been designed to enhance student understanding and to facilitate
creative instruction.
n Ancillaries for Instructors
Instructor’s Guide
by Douglas Shaw
Each section of the text is discussed from several viewpoints. Available online at the Instructor’s Companion Site, the Instructor’s Guide contains suggested time to allot, points to stress,
text discussion topics, core materials for lecture, workshop / discussion suggestions, group work
exercises in a form suitable for handout, and suggested homework assignments.
Complete Solutions Manual
Single Variable Calculus: Early Transcendentals, Ninth Edition
Chapters 1–11
By Joshua Babbin, Scott Barnett, and Jeffery A. Cole
Multivariable Calculus, Ninth Edition
Chapters 10 –16
By Joshua Babbin and Gina Sanders
Includes worked-out solutions to all exercises in the text. Both volumes of the Complete Solutions Manual are available online at the Instructor’s Companion Site.
Test Bank
Contains text-specific multiple-choice and free response test items and is available online at the
Instructor’s Companion Site.
Cengage Learning Testing
Powered by Cognero
This flexible online system allows you to author, edit, and manage test bank content; create
multiple test versions in an instant; and deliver tests from your LMS, your classroom, or
wherever you want.
n Ancillaries for Instructors and Students
Stewart Website
StewartCalculus.com
Homework Hints n Algebra Review
Challenge Problems n Web links n
WebAssign®
Single-term Access to WebAssign
Printed Access Code: ISBN 978-0-357-12892-3
Instant Access Code: ISBN 978-0-357-12891-6
Additional Topics n
History of Mathematics
n
Drill exercises
n
Multi-term Access to WebAssign
Printed Access Code: ISBN 978-0-357-12894-7
Instant Access Code: ISBN 978-0-357-12893-0
Prepare for class with confidence using WebAssign from Cengage. This online learning
platform—which includes an interactive ebook—fuels practice, so you absorb what you learn
and prepare better for tests. Videos and tutorials walk you through concepts and deliver instant
feedback and grading, so you always know where you stand in class. Focus your study time and
get extra practice where you need it most. Study smarter! Ask your instructor today how you can
get access to WebAssign, or learn about self-study options at Cengage.com/WebAssign.
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
xviii
PREFACE
n Ancillaries for Students
Student Solutions Manual
Single Variable Calculus Early Transcendentals Ninth Edition
Chapters 1–11
By Joshua Babbin, Scott Barnett, and Jeffery A. Cole
ISBN 978-0-357-02238-2
Multivariable Calculus Ninth Edition
Chapters 10–16
By Joshua Babbin and Gina Sanders
ISBN 978-0-357-04315-8
Provides worked-out solutions to all odd-numbered exercises in the text, giving students a
chance to check their answer and ensure they took the correct steps to arrive at the answer.
Both volumes of the Student Solutions Manual can be ordered or accessed online as an
eBook at Cengage.com by searching the ISBN.
Acknowledgments
One of the main factors aiding in the preparation of this edition is the cogent advice
from a large number of reviewers, all of whom have extensive experience teaching calculus. We greatly appreciate their suggestions and the time they spent to understand the
approach taken in this book. We have learned something from each of them.
n Ninth Edition Reviewers
Malcolm Adams, University of Georgia
Ulrich Albrecht, Auburn University
Bonnie Amende, Saint Martin’s University
Champike Attanayake, Miami University Middletown
Amy Austin, Texas A&M University
Elizabeth Bowman, University of Alabama
Joe Brandell, West Bloomfield High School / Oakland University
Lorraine Braselton, Georgia Southern University
Mark Brittenham, University of Nebraska – Lincoln
Michael Ching, Amherst College
Kwai-Lee Chui, University of Florida
Arman Darbinyan, Vanderbilt University
Roger Day, Illinois State University
Toka Diagana, Howard University
Karamatu Djima, Amherst College
Mark Dunster, San Diego State University
Eric Erdmann, University of Minnesota – Duluth
Debra Etheridge, The University of North Carolina at Chapel Hill
Jerome Giles, San Diego State University
Mark Grinshpon, Georgia State University
Katie Gurski, Howard University
John Hall, Yale University
David Hemmer, University at Buffalo – SUNY, N. Campus
Frederick Hoffman, Florida Atlantic University
Keith Howard, Mercer University
Iztok Hozo, Indiana University Northwest
Shu-Jen Huang, University of Florida
Matthew Isom, Arizona State University – Polytechnic
James Kimball, University of Louisiana at Lafayette
Thomas Kinzel, Boise State University
Anastasios Liakos, United States Naval Academy
Chris Lim, Rutgers University – Camden
Jia Liu, University of West Florida
Joseph Londino, University of Memphis
Colton Magnant, Georgia Southern University
Mark Marino, University at Buffalo – SUNY, N. Campus
Kodie Paul McNamara, Georgetown University
Mariana Montiel, Georgia State University
Russell Murray, Saint Louis Community College
Ashley Nicoloff, Glendale Community College
Daniella Nokolova-Popova, Florida Atlantic University
Giray Okten, Florida State University – Tallahassee
Aaron Peterson, Northwestern University
Alice Petillo, Marymount University
Mihaela Poplicher, University of Cincinnati
Cindy Pulley, Illinois State University
Russell Richins, Thiel College
Lorenzo Sadun, University of Texas at Austin
Michael Santilli, Mesa Community College
Christopher Shaw, Columbia College
Brian Shay, Canyon Crest Academy
Mike Shirazi, Germanna Community College – Fredericksburg
Pavel Sikorskii, Michigan State University
Mary Smeal, University of Alabama
Edwin Smith, Jacksonville State University
Sandra Spiroff, University of Mississippi
Stan Stascinsky, Tarrant County College
Jinyuan Tao, Loyola University of Maryland
Ilham Tayahi, University of Memphis
Michael Tom, Louisiana State University – Baton Rouge
Michael Westmoreland, Denison University
Scott Wilde, Baylor University
Larissa Williamson, University of Florida
Michael Yatauro, Penn State Brandywine
Gang Yu, Kent State University
Loris Zucca, Lone Star College – Kingwood
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PREFACE
xix
n Previous Edition Reviewers
Jay Abramson, Arizona State University
B. D. Aggarwala, University of Calgary
John Alberghini, Manchester Community College
Michael Albert, Carnegie-Mellon University
Daniel Anderson, University of Iowa
Maria Andersen, Muskegon Community College
Eric Aurand, Eastfield College
Amy Austin, Texas A&M University
Donna J. Bailey, Northeast Missouri State University
Wayne Barber, Chemeketa Community College
Joy Becker, University of Wisconsin – Stout
Marilyn Belkin, Villanova University
Neil Berger, University of Illinois, Chicago
David Berman, University of New Orleans
Anthony J. Bevelacqua, University of North Dakota
Richard Biggs, University of Western Ontario
Robert Blumenthal, Oglethorpe University
Martina Bode, Northwestern University
Przemyslaw Bogacki, Old Dominion University
Barbara Bohannon, Hofstra University
Jay Bourland, Colorado State University
Adam Bowers, University of California San Diego
Philip L. Bowers, Florida State University
Amy Elizabeth Bowman, University of Alabama in Huntsville
Stephen W. Brady, Wichita State University
Michael Breen, Tennessee Technological University
Monica Brown, University of Missouri – St. Louis
Robert N. Bryan, University of Western Ontario
David Buchthal, University of Akron
Roxanne Byrne, University of Colorado at Denver and
Health Sciences Center
Jenna Carpenter, Louisiana Tech University
Jorge Cassio, Miami-Dade Community College
Jack Ceder, University of California, Santa Barbara
Scott Chapman, Trinity University
Zhen-Qing Chen, University of Washington – Seattle
James Choike, Oklahoma State University
Neena Chopra, The Pennsylvania State University
Teri Christiansen, University of Missouri – Columbia
Barbara Cortzen, DePaul University
Carl Cowen, Purdue University
Philip S. Crooke, Vanderbilt University
Charles N. Curtis, Missouri Southern State College
Daniel Cyphert, Armstrong State College
Robert Dahlin
Bobby Dale Daniel, Lamar University
Jennifer Daniel, Lamar University
M. Hilary Davies, University of Alaska Anchorage
Gregory J. Davis, University of Wisconsin – Green Bay
Elias Deeba, University of Houston – Downtown
Daniel DiMaria, Suffolk Community College
Seymour Ditor, University of Western Ontario
Edward Dobson, Mississippi State University
Andras Domokos, California State University, Sacramento
Greg Dresden, Washington and Lee University
Daniel Drucker, Wayne State University
Kenn Dunn, Dalhousie University
Dennis Dunninger, Michigan State University
Bruce Edwards, University of Florida
David Ellis, San Francisco State University
John Ellison, Grove City College
Martin Erickson, Truman State University
Garret Etgen, University of Houston
Theodore G. Faticoni, Fordham University
Laurene V. Fausett, Georgia Southern University
Norman Feldman, Sonoma State University
Le Baron O. Ferguson, University of California – Riverside
Newman Fisher, San Francisco State University
Timothy Flaherty, Carnegie Mellon University
José D. Flores, The University of South Dakota
William Francis, Michigan Technological University
James T. Franklin, Valencia Community College, East
Stanley Friedlander, Bronx Community College
Patrick Gallagher, Columbia University – New York
Paul Garrett, University of Minnesota – Minneapolis
Frederick Gass, Miami University of Ohio
Lee Gibson, University of Louisville
Bruce Gilligan, University of Regina
Matthias K. Gobbert, University of Maryland, Baltimore County
Gerald Goff, Oklahoma State University
Isaac Goldbring, University of Illinois at Chicago
Jane Golden, Hillsborough Community College
Stuart Goldenberg, California Polytechnic State University
John A. Graham, Buckingham Browne & Nichols School
Richard Grassl, University of New Mexico
Michael Gregory, University of North Dakota
Charles Groetsch, University of Cincinnati
Semion Gutman, University of Oklahoma
Paul Triantafilos Hadavas, Armstrong Atlantic State University
Salim M. Haïdar, Grand Valley State University
D. W. Hall, Michigan State University
Robert L. Hall, University of Wisconsin – Milwaukee
Howard B. Hamilton, California State University, Sacramento
Darel Hardy, Colorado State University
Shari Harris, John Wood Community College
Gary W. Harrison, College of Charleston
Melvin Hausner, New York University/Courant Institute
Curtis Herink, Mercer University
Russell Herman, University of North Carolina at Wilmington
Allen Hesse, Rochester Community College
Diane Hoffoss, University of San Diego
Randall R. Holmes, Auburn University
Lorraine Hughes, Mississippi State University
James F. Hurley, University of Connecticut
Amer Iqbal, University of Washington – Seattle
Matthew A. Isom, Arizona State University
Jay Jahangiri, Kent State University
Gerald Janusz, University of Illinois at Urbana-Champaign
John H. Jenkins, Embry-Riddle Aeronautical University,
Prescott Campus
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xx
PREFACE
Lea Jenkins, Clemson University
John Jernigan, Community College of Philadelphia
Clement Jeske, University of Wisconsin, Platteville
Carl Jockusch, University of Illinois at Urbana-Champaign
Jan E. H. Johansson, University of Vermont
Jerry Johnson, Oklahoma State University
Zsuzsanna M. Kadas, St. Michael’s College
Brian Karasek, South Mountain Community College
Nets Katz, Indiana University Bloomington
Matt Kaufman
Matthias Kawski, Arizona State University
Frederick W. Keene, Pasadena City College
Robert L. Kelley, University of Miami
Akhtar Khan, Rochester Institute of Technology
Marianne Korten, Kansas State University
Virgil Kowalik, Texas A&I University
Jason Kozinski, University of Florida
Kevin Kreider, University of Akron
Leonard Krop, DePaul University
Carole Krueger, The University of Texas at Arlington
Mark Krusemeyer, Carleton College
Ken Kubota, University of Kentucky
John C. Lawlor, University of Vermont
Christopher C. Leary, State University of New York at Geneseo
David Leeming, University of Victoria
Sam Lesseig, Northeast Missouri State University
Phil Locke, University of Maine
Joyce Longman, Villanova University
Joan McCarter, Arizona State University
Phil McCartney, Northern Kentucky University
Igor Malyshev, San Jose State University
Larry Mansfield, Queens College
Mary Martin, Colgate University
Nathaniel F. G. Martin, University of Virginia
Gerald Y. Matsumoto, American River College
James McKinney, California State Polytechnic University, Pomona
Tom Metzger, University of Pittsburgh
Richard Millspaugh, University of North Dakota
John Mitchell, Clark College
Lon H. Mitchell, Virginia Commonwealth University
Michael Montaño, Riverside Community College
Teri Jo Murphy, University of Oklahoma
Martin Nakashima, California State Polytechnic University,
Pomona
Ho Kuen Ng, San Jose State University
Richard Nowakowski, Dalhousie University
Hussain S. Nur, California State University, Fresno
Norma Ortiz-Robinson, Virginia Commonwealth University
Wayne N. Palmer, Utica College
Vincent Panico, University of the Pacific
F. J. Papp, University of Michigan – Dearborn
Donald Paul, Tulsa Community College
Mike Penna, Indiana University – Purdue University Indianapolis
Chad Pierson, University of Minnesota, Duluth
Mark Pinsky, Northwestern University
Lanita Presson, University of Alabama in Huntsville
Lothar Redlin, The Pennsylvania State University
Karin Reinhold, State University of New York at Albany
Thomas Riedel, University of Louisville
Joel W. Robbin, University of Wisconsin – Madison
Lila Roberts, Georgia College and State University
E. Arthur Robinson, Jr., The George Washington University
Richard Rockwell, Pacific Union College
Rob Root, Lafayette College
Richard Ruedemann, Arizona State University
David Ryeburn, Simon Fraser University
Richard St. Andre, Central Michigan University
Ricardo Salinas, San Antonio College
Robert Schmidt, South Dakota State University
Eric Schreiner, Western Michigan University
Christopher Schroeder, Morehead State University
Mihr J. Shah, Kent State University – Trumbull
Angela Sharp, University of Minnesota, Duluth
Patricia Shaw, Mississippi State University
Qin Sheng, Baylor University
Theodore Shifrin, University of Georgia
Wayne Skrapek, University of Saskatchewan
Larry Small, Los Angeles Pierce College
Teresa Morgan Smith, Blinn College
William Smith, University of North Carolina
Donald W. Solomon, University of Wisconsin – Milwaukee
Carl Spitznagel, John Carroll University
Edward Spitznagel, Washington University
Joseph Stampfli, Indiana University
Kristin Stoley, Blinn College
Mohammad Tabanjeh, Virginia State University
Capt. Koichi Takagi, United States Naval Academy
M. B. Tavakoli, Chaffey College
Lorna TenEyck, Chemeketa Community College
Magdalena Toda, Texas Tech University
Ruth Trygstad, Salt Lake Community College
Paul Xavier Uhlig, St. Mary’s University, San Antonio
Stan Ver Nooy, University of Oregon
Andrei Verona, California State University – Los Angeles
Klaus Volpert, Villanova University
Rebecca Wahl, Butler University
Russell C. Walker, Carnegie-Mellon University
William L. Walton, McCallie School
Peiyong Wang, Wayne State University
Jack Weiner, University of Guelph
Alan Weinstein, University of California, Berkeley
Roger Werbylo, Pima Community College
Theodore W. Wilcox, Rochester Institute of Technology
Steven Willard, University of Alberta
David Williams, Clayton State University
Robert Wilson, University of Wisconsin – Madison
Jerome Wolbert, University of Michigan – Ann Arbor
Dennis H. Wortman, University of Massachusetts, Boston
Mary Wright, Southern Illinois University – Carbondale
Paul M. Wright, Austin Community College
Xian Wu, University of South Carolina
Zhuan Ye, Northern Illinois University
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PREFACE
xxi
We thank all those who have contributed to this edition—and there are many—as
well as those whose input in previous editions lives on in this new edition. We thank
Marigold Ardren, David Behrman, George Bergman, R. B. Burckel, Bruce Colletti,
John Dersch, Gove Effinger, Bill Emerson, Alfonso Gracia-Saz, Jeffery Hayen, Dan
Kalman, Quyan Khan, John Khoury, Allan MacIsaac, Tami Martin, Monica Nitsche,
Aaron Peterson, Lamia Raffo, Norton Starr, Jim Trefzger, Aaron Watson, and Weihua
Zeng for their suggestions; Joseph Bennish, Craig Chamberlin, Kent Merryfield, and
Gina Sanders for insightful conversations on calculus; Al Shenk and Dennis Zill for permission to use exercises from their calculus texts; COMAP for permission to use project
material; David Bleecker, Victor Kaftal, Anthony Lam, Jamie Lawson, Ira Rosenholtz,
Paul Sally, Lowell Smylie, Larry Wallen, and Jonathan Watson for ideas for exercises;
Dan Drucker for the roller derby project; Thomas Banchoff, Tom Farmer, Fred Gass,
John Ramsay, Larry Riddle, Philip Straffin, and Klaus Volpert for ideas for projects;
Josh Babbin, Scott Barnett, and Gina Sanders for solving the new exercises and suggesting ways to improve them; Jeff Cole for overseeing all the solutions to the exercises
and ensuring their correctness; Mary Johnson and Marv Riedesel for accuracy in proofreading, and Doug Shaw for accuracy checking. In addition, we thank Dan Anderson,
Ed Barbeau, Fred Brauer, Andy Bulman-Fleming, Bob Burton, David Cusick, Tom
DiCiccio, Garret Etgen, Chris Fisher, Barbara Frank, Leon Gerber, Stuart Goldenberg,
Arnold Good, Gene Hecht, Harvey Keynes, E. L. Koh, Zdislav Kovarik, Kevin Kreider, Emile LeBlanc, David Leep, Gerald Leibowitz, Larry Peterson, Mary Pugh, Carl
Riehm, John Ringland, Peter Rosenthal, Dusty Sabo, Dan Silver, Simon Smith, Alan
Weinstein, and Gail Wolkowicz.
We are grateful to Phyllis Panman for assisting us in preparing the manuscript, solving the exercises and suggesting new ones, and for critically proofreading the entire
manuscript.
We are deeply indebted to our friend and colleague Lothar Redlin who began working with us on this revision shortly before his untimely death in 2018. Lothar’s deep
insights into mathematics and its pedagogy, and his lightning fast problem-solving
skills, were invaluable assets.
We especially thank Kathi Townes of TECHarts, our production service and copyeditor (for this as well as the past several editions). Her extraordinary ability to recall
any detail of the manuscript as needed, her facility in simultaneously handling different editing tasks, and her comprehensive familiarity with the book were key factors in
its accuracy and timely production. We also thank Lori Heckelman for the elegant and
precise rendering of the new illustrations.
At Cengage Learning we thank Timothy Bailey, Teni Baroian, Diane Beasley, Carly
Belcher, Vernon Boes, Laura Gallus, Stacy Green, Justin Karr, Mark Linton, Samantha
Lugtu, Ashley Maynard, Irene Morris, Lynh Pham, Jennifer Risden, Tim Rogers, Mark
Santee, Angela Sheehan, and Tom Ziolkowski. They have all done an outstanding job.
This textbook has benefited greatly over the past three decades from the advice and
guidance of some of the best mathematics editors: Ron Munro, Harry Campbell, Craig
Barth, Jeremy Hayhurst, Gary Ostedt, Bob Pirtle, Richard Stratton, Liz Covello, Neha
Taleja, and now Gary Whalen. They have all contributed significantly to the success
of this book. Prominently, Gary Whalen’s broad knowledge of current issues in the
teaching of mathematics and his continual research into creating better ways of using
technology as a teaching and learning tool were invaluable resources in the creation of
this edition.
JA M E S S T E WA RT
DA N I E L C L E G G
S A L E E M WAT S O N
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A Tribute to James Stewart
james stewart had a singular gift for teaching mathematics. The large lecture
halls where he taught his calculus classes were always packed to capacity with students,
whom he held engaged with interest and anticipation as he led them to discover a new
concept or the solution to a stimulating problem. Stewart presented calculus the way
he viewed it — as a rich subject with intuitive concepts, wonderful problems, powerful applications, and a fascinating history. As a testament to his success in teaching
and lecturing, many of his students went on to become mathematicians, scientists, and
engineers — and more than a few are now university professors themselves. It was his
students who first suggested that he write a calculus textbook of his own. Over the years,
former students, by then working scientists and engineers, would call him to discuss
mathematical problems that they encountered in their work; some of these discussions
resulted in new exercises or projects in the book.
We each met James Stewart—or Jim as he liked us to call him—through his teaching
and lecturing, resulting in his inviting us to coauthor mathematics textbooks with him.
In the years we have known him, he was in turn our teacher, mentor, and friend.
Jim had several special talents whose combination perhaps uniquely qualified him
to write such a beautiful calculus textbook — a textbook with a narrative that speaks to
students and that combines the fundamentals of calculus with conceptual insights on
how to think about them. Jim always listened carefully to his students in order to find
out precisely where they may have had difficulty with a concept. Crucially, Jim really
enjoyed hard work — a necessary trait for completing the immense task of writing a
calculus book. As his coauthors, we enjoyed his contagious enthusiasm and optimism,
making the time we spent with him always fun and productive, never stressful.
Most would agree that writing a calculus textbook is a major enough feat for one
lifetime, but amazingly, Jim had many other interests and accomplishments: he played
violin professionally in the Hamilton and McMaster Philharmonic Orchestras for many
years, he had an enduring passion for architecture, he was a patron of the arts and cared
deeply about many social and humanitarian causes. He was also a world traveler, an
eclectic art collector, and even a gourmet cook.
James Stewart was an extraordinary person, mathematician, and teacher. It has been
our honor and privilege to be his coauthors and friends.
DA N I E L C L E G G
S A L E E M WAT S O N
xxii
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About the Authors
For more than two decades, Daniel Clegg and Saleem Watson have worked with James
Stewart on writing mathematics textbooks. The close working relationship between
them was particularly productive because they shared a common viewpoint on teaching
mathematics and on writing mathematics. In a 2014 interview James Stewart remarked
on their collaborations: “We discovered that we could think in the same way . . . we
agreed on almost everything, which is kind of rare.”
Daniel Clegg and Saleem Watson met James Stewart in different ways, yet in each
case their initial encounter turned out to be the beginning of a long association. Stewart
spotted Daniel’s talent for teaching during a chance meeting at a mathematics conference and asked him to review the manuscript for an upcoming edition of Calculus and
to author the multivariable solutions manual. Since that time Daniel has played an everincreasing role in the making of several editions of the Stewart calculus books. He and
Stewart have also coauthored an applied calculus textbook. Stewart first met Saleem
when Saleem was a student in his graduate mathematics class. Later Stewart spent a
sabbatical leave doing research with Saleem at Penn State University, where Saleem
was an instructor at the time. Stewart asked Saleem and Lothar Redlin (also a student of
Stewart’s) to join him in writing a series of precalculus textbooks; their many years of
collaboration resulted in several editions of these books.
james stewart was professor of mathematics at McMaster University and the
University of Toronto for many years. James did graduate studies at Stanford University and the University of Toronto, and subsequently did research at the University of
London. His research field was Harmonic Analysis and he also studied the connections
between mathematics and music.
daniel clegg is professor of mathematics at Palomar College in Southern California. He did undergraduate studies at California State University, Fullerton and
graduate studies at the University of California, Los Angeles (UCLA). Daniel is a
consummate teacher; he has been teaching mathematics ever since he was a graduate
student at UCLA.
saleem watson is professor emeritus of mathematics at California State University,
Long Beach. He did undergraduate studies at Andrews University in Michigan and
graduate studies at Dalhousie University and McMaster University. After completing
a research fellowship at the University of Warsaw, he taught for several years at Penn
State before joining the mathematics department at California State University, Long
Beach.
Stewart and Clegg have published Brief Applied Calculus.
Stewart, Redlin, and Watson have published Precalculus: Mathematics for
Calculus, College Algebra, Trigonometry, Algebra and Trigonometry, and (with Phyllis
Panman) College Algebra: Concepts and Contexts.
xxiii
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Technology in the Ninth Edition
Graphing and computing devices are valuable tools for learning and exploring calculus,
and some have become well established in calculus instruction. Graphing calculators are
useful for drawing graphs and performing some numerical calculations, like approximating solutions to equations or numerically evaluating derivatives (Chapter 3) or definite integrals (Chapter 5). Mathematical software packages called computer algebra
systems (CAS, for short) are more powerful tools. Despite the name, algebra represents
only a small subset of the capabilities of a CAS. In particular, a CAS can do mathematics symbolically rather than just numerically. It can find exact solutions to equations and
exact formulas for derivatives and integrals.
We now have access to a wider variety of tools of varying capabilities than ever
before. These include Web-based resources (some of which are free of charge) and
apps for smartphones and tablets. Many of these resources include at least some CAS
functionality, so some exercises that may have typically required a CAS can now be
completed using these alternate tools.
In this edition, rather than refer to a specific type of device (a graphing calculator, for
instance) or software package (such as a CAS), we indicate the type of capability that is
needed to work an exercise.
;
Graphing Icon
The appearance of this icon beside an exercise indicates that you are expected to use a
machine or software to help you draw the graph. In many cases, a graphing calculator
will suffice. Websites such as Desmos.com provide similar capability. If the graph is in
3D (see Chapters 12 – 16), WolframAlpha.com is a good resource. There are also many
graphing software applications for computers, smartphones, and tablets. If an exercise
asks for a graph but no graphing icon is shown, then you are expected to draw the graph
by hand. In Chapter 1 we review graphs of basic functions and discuss how to use transformations to graph modified versions of these basic functions.
Technology Icon
This icon is used to indicate that software or a device with abilities beyond just graphing
is needed to complete the exercise. Many graphing calculators and software resources
can provide numerical approximations when needed. For working with mathematics
symbolically, websites like WolframAlpha.com or Symbolab.com are helpful, as are
more advanced graphing calculators such as the Texas Instrument TI-89 or TI-Nspire
CAS. If the full power of a CAS is needed, this will be stated in the exercise, and access
to software packages such as Mathematica, Maple, MATLAB, or SageMath may be
required. If an exercise does not include a technology icon, then you are expected to
evaluate limits, derivatives, and integrals, or solve equations by hand, arriving at exact
answers. No technology is needed for these exercises beyond perhaps a basic scientific
calculator.
xxiv
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To the Student
Reading a calculus textbook is different from reading a story or a news article. Don’t
be discouraged if you have to read a passage more than once in order to understand it.
You should have pencil and paper and calculator at hand to sketch a diagram or make a
calculation.
Some students start by trying their homework problems and read the text only if they
get stuck on an exercise. We suggest that a far better plan is to read and understand a
section of the text before attempting the exercises. In particular, you should look at the
definitions to see the exact meanings of the terms. And before you read each example,
we suggest that you cover up the solution and try solving the problem yourself.
Part of the aim of this course is to train you to think logically. Learn to write the
solutions of the exercises in a connected, step-by-step fashion with explanatory
sentences — not just a string of disconnected equations or formulas.
The answers to the odd-numbered exercises appear at the back of the book, in Appendix H. Some exercises ask for a verbal explanation or interpretation or description. In
such cases there is no single correct way of expressing the answer, so don’t worry that
you haven’t found the definitive answer. In addition, there are often several different
forms in which to express a numerical or algebraic answer, so if your answer differs
from the given one, don’t immediately assume you’re wrong. For example, if the answer
given in the back of the book is s2 2 1 and you obtain 1y(1 1 s2 ), then you’re correct and rationalizing the denominator will show that the answers are equivalent.
The icon ; indicates an exercise that definitely requires the use of either a graphing calculator or a computer with graphing software to help you sketch the graph. But
that doesn’t mean that graphing devices can’t be used to check your work on the other
exercises as well. The symbol
indicates that technological assistance beyond just
graphing is needed to complete the exercise. (See Technology in the Ninth Edition for
more details.)
You will also encounter the symbol , which warns you against committing an error.
This symbol is placed in the margin in situations where many students tend to make the
same mistake.
Homework Hints are available for many exercises. These hints can be found on
StewartCalculus.com as well as in WebAssign. The homework hints ask you questions that allow you to make progress toward a solution without actually giving you the
answer. If a particular hint doesn’t enable you to solve the problem, you can click to
reveal the next hint.
We recommend that you keep this book for reference purposes after you finish the
course. Because you will likely forget some of the specific details of calculus, the book
will serve as a useful reminder when you need to use calculus in subsequent courses.
And, because this book contains more material than can be covered in any one course, it
can also serve as a valuable resource for a working scientist or engineer.
Calculus is an exciting subject, justly considered to be one of the greatest achievements of the human intellect. We hope you will discover that it is not only useful but
also intrinsically beautiful.
xxv
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Diagnostic Tests
Success in calculus depends to a large extent on knowledge of the mathematics that
precedes calculus: algebra, analytic geometry, functions, and trigonometry. The following tests are intended to diagnose weaknesses that you might have in these areas. After
taking each test you can check your answers against the given answers and, if necessary,
refresh your skills by referring to the review materials that are provided.
A Diagnostic Test: Algebra
. Evaluate each expression without using a calculator.
(a) s23d4
(b) 234
(c) 324
(d)
5 23
5 21
(e)
SD
2
3
22
(f) 16 23y4
. Simplify each expression. Write your answer without negative exponents.
(a) s200 2 s32
(b) s3a 3b 3 ds4ab 2 d 2
(c)
S
3x 3y2 y 3
x 2 y21y2
D
22
. Expand and simplify.
(a) 3sx 1 6d 1 4s2x 2 5d
(b) sx 1 3ds4x 2 5d
(c) (sa 1 sb )(sa 2 sb )
(d) s2x 1 3d2
(e) sx 1 2d3
. Factor each expression.
(a) 4x 2 2 25
(b) 2x 2 1 5x 2 12
(c) x 3 2 3x 2 2 4x 1 12
(d) x 4 1 27x
(e) 3x 3y2 2 9x 1y2 1 6x 21y2
(f) x 3 y 2 4xy
. Simplify the rational expression.
(a)
x 2 1 3x 1 2
x2 2 x 2 2
2
(c)
x
x11
2
x2 2 4
x12
(b)
2x 2 2 x 2 1
x13
!
2
x 29
2x 1 1
y
x
2
x
y
(d)
1
1
2
y
x
xxvi
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
xxvii
DIAGNOSTIC TESTS
. Rationalize the expression and simplify.
s10
(a)
(b)
s5 2 2
. Rewrite by completing the square.
(a) x 2 1 x 1 1
s4 1 h 2 2
h
(b) 2x 2 2 12x 1 11
. Solve the equation. (Find only the real solutions.)
2x
2x 2 1
−
x11
x
(a) x 1 5 − 14 2 12 x
(b)
(c) x 2 2 x 2 12 − 0
(d) 2x 2 1 4x 1 1 − 0
(e) x 4 2 3x 2 1 2 − 0
(f) 3 x 2 4 − 10
(g) 2xs4 2 xd
21y2
|
2 3 s4 2 x − 0
|
. Solve each inequality. Write your answer using interval notation.
(a) 24 , 5 2 3x < 17
(b) x 2 , 2x 1 8
(c) xsx 2 1dsx 1 2d . 0
(d) x 2 4 , 3
|
2x 2 3
(e)
<1
x11
|
. State whether each equation is true or false.
(a) s p 1 qd2 − p 2 1 q 2
(b) sab − sa sb
(c) sa 2 1 b 2 − a 1 b
(d)
1 1 TC
−11T
C
1
1
1
− 2
x2y
x
y
(f)
1yx
1
−
ayx 2 byx
a2b
(e)
ANSWERS TO DIAGNOSTIC TEST A: ALGEBRA
1
(c) 81
. (a) 81
(b) 281
(d) 25
9
4
(f )
1
8
(b) 48a 5b7
(c)
x
9y7
. (a) 6s2
(e)
. (a) 11x 2 2
(b) 4x 2 1 7x 2 15
(c) a 2 b
(d) 4x 2 1 12x 1 9
3
2
(e) x 1 6x 1 12x 1 8
. (a) s2x 2 5ds2x 1 5d
(c) sx 2 3dsx 2 2dsx 1 2d
(e) 3x21y2sx 2 1dsx 2 2d
x12
x22
1
(c)
x22
. (a)
(b) s2x 2 3dsx 1 4d
(d) xsx 1 3dsx 2 2 3x 1 9d
(f) xysx 2 2dsx 1 2d
(b)
x21
x23
(d) 2sx 1 yd
1
. (a) 5s2 1 2s10
(b)
. (a) ( x 1 12 ) 1 34
(b) 2sx 2 3d2 2 7
2
. (a) 6
(d)
(g)
21 6 12 s2
12
5
(b) 1
(c) 23, 4
(e) 61, 6s2
(f) 23 , 22
3
. (a) f24, 3d
(c) s22, 0d ø s1, `d
(e) s21, 4g
. (a) False
(d) False
s4 1 h 1 2
(b) s22, 4d
(d) s1, 7d
(b) True
(e) False
(c) False
(f) True
If you had difficulty with these problems, you may wish to consult the
Review of Algebra on the website StewartCalculus.com.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
xxviii
DIAGNOSTIC TESTS
B Diagnostic Test: Analytic Geometry
. Find an equation for the line that passes through the point s2, 25d and
(a) has slope 23
(b) is parallel to the x-axis
(c) is parallel to the y-axis
(d) is parallel to the line 2x 2 4y − 3
. Find an equation for the circle that has center s21, 4d and passes through the point s3, 22d.
. Find the center and radius of the circle with equation x 2 1 y 2 2 6x 1 10y 1 9 − 0.
. Let As27, 4d and Bs5, 212d be points in the plane.
(a) Find the slope of the line that contains A and B.
(b) Find an equation of the line that passes through A and B. What are the intercepts?
(c) Find the midpoint of the segment AB.
(d) Find the length of the segment AB.
(e) Find an equation of the perpendicular bisector of AB.
(f) Find an equation of the circle for which AB is a diameter.
. Sketch the region in the xy-plane defined by the equation or inequalities.
(a) 21 < y < 3
(c)
(b)
y , 1 2 12 x
| x | , 4 and | y | , 2
(d) y > x 2 2 1
(e) x 2 1 y 2 , 4
(f) 9x 2 1 16y 2 − 144
ANSWERS TO DIAGNOSTIC TEST B: ANALYTIC GEOMETRY
. (a) y − 23x 1 1
(c) x − 2
(b) y − 25
(d)
y − 12 x 2 6
.
(a)
y
(b)
3
. sx 1 1d2 1 s y 2 4d2 − 52
x
_1
. (a) 234
(b) 4x 1 3y 1 16 − 0; x-intercept 24, y-intercept 2 16
3
(c) s21, 24d
(d) 20
(e) 3x 2 4y − 13
(f ) sx 1 1d2 1 s y 1 4d2 − 100
(d)
_4
1
1
4x
0
(e)
y
2
0
y
0
y=1- 2 x
2
x
_2
y
_1
(c)
2
0
. Center s3, 25d, radius 5
y
1
x
0
y=≈-1
(f)
≈+¥=4
2
x
y
3
0
4 x
If you had difficulty with these problems, you may wish to consult
the review of analytic geometry in Appendixes B and C.
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xxix
DIAGNOSTIC TESTS
C Diagnostic Test: Functions
y
. The graph of a function f is given at the left.
(a) State the value of f s21d.
(b) Estimate the value of f s2d.
(c) For what values of x is f sxd − 2?
(d) Estimate the values of x such that f sxd − 0.
(e) State the domain and range of f .
1
0
1
x
. If f sxd − x 3, evaluate the difference quotient
f s2 1 hd 2 f s2d
and simplify your answer.
h
. Find the domain of the function.
FIGURE FOR PROBLEM 1
(a) f sxd −
2x 1 1
x2 1 x 2 2
(b) tsxd −
3
x
s
x2 1 1
(c) hsxd − s4 2 x 1 sx 2 2 1
. How are graphs of the functions obtained from the graph of f ?
(a) y − 2f sxd
(b) y − 2 f sxd 2 1
(c) y − f sx 2 3d 1 2
. Without using a calculator, make a rough sketch of the graph.
(a) y − x 3
(b) y − sx 1 1d3
(c) y − sx 2 2d3 1 3
(d) y − 4 2 x 2
(e) y − sx
(f) y − 2 sx
x
21
(g) y − 22
(h) y − 1 1 x
. Let f sxd −
H
1 2 x 2 if x < 0
2x 1 1 if x . 0
(a) Evaluate f s22d and f s1d.
(b) Sketch the graph of f .
. If f sxd − x 2 1 2x 2 1 and tsxd − 2x 2 3, find each of the following functions.
(a) f 8 t
(b) t 8 f
(c) t 8 t 8 t
ANSWERS TO DIAGNOSTIC TEST C: FUNCTIONS
. (a) 22
(c) 23, 1
(e) f23, 3g, f22, 3g
(b) 2.8
(d) 22.5, 0.3
5. (a)
0
. (a) Reflect about the x-axis
(b) Stretch vertically by a factor of 2, then shift 1 unit
downward
(c) Shift 3 units to the right and 2 units upward
(d)
(g)
1
x
_1
(e)
2
x
x
0
1
x
1
x
x
0
(f)
y
0
(h)
y
y
0
1
y
1
0
_1
(2, 3)
1
y
4
0
(c) y
y
1
. 12 1 6h 1 h 2
. (a) s2`, 22d ø s22, 1d ø s1, `d
(b) s2`, `d
(c) s2`, 21g ø f1, 4g
(b)
y
1
x
0
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x
xxx
DIAGNOSTIC TESTS
6. (a) 23, 3
(b)
_1
y
. (a) s f 8 tdsxd − 4x 2 2 8x 1 2
1
(b) s t 8 f dsxd − 2x 2 1 4x 2 5
(c) s t 8 t 8 tdsxd − 8x 2 21
x
0
If you had difficulty with these problems, you should look at sections 1.1–1.3 of this book.
D Diagnostic Test: Trigonometry
. Convert from degrees to radians.
(a) 3008
(b) 2188
. Convert from radians to degrees.
(a) 5!y6
(b) 2
. Find the length of an arc of a circle with radius 12 cm if the arc subtends a central angle
of 308.
. Find the exact values.
(a) tans!y3d
(b) sins7!y6d
24
¨
(c) secs5!y3d
. Express the lengths a and b in the figure in terms of ".
a
. If sin x − 13 and sec y − 54, where x and y lie between 0 and !y2, evaluate sinsx 1 yd.
. Prove the identities.
b
(a) tan " sin " 1 cos " − sec "
FIGURE FOR PROBLEM 5
(b)
2 tan x
− sin 2x
1 1 tan 2x
. Find all values of x such that sin 2x − sin x and 0 < x < 2!.
. Sketch the graph of the function y − 1 1 sin 2x without using a calculator.
ANSWERS TO DIAGNOSTIC TEST D: TRIGONOMETRY
. (a) 5!y3
(b) 2!y10
. (a) 1508
(b) 3608y! < 114.68
. 2! cm
. (a) s3
1
. 15
(4 1 6 s2 )
. 0, !y3, !, 5!y3, 2!
y
.
(b)
221
2
(c) 2
. a − 24 sin ", b − 24 cos "
_π
0
π
x
If you had difficulty with these problems, you should look at Appendix D of this book.
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By the time you finish this course, you will be able to determine where a pilot should start descent for a smooth landing,
find the length of the curve used to design the Gateway Arch in St. Louis, compute the force on a baseball bat when it
strikes the ball, predict the population sizes for competing predator-prey species, show that bees form the cells of a
beehive in a way that uses the least amount of wax, and estimate the amount of fuel needed to propel a rocket into orbit.
Top row: Who is Danny / Shutterstock.com; iStock.com / gnagel; Richard Paul Kane / Shutterstock.com
Bottom row: Bruce Ellis / Shutterstock.com; Kostiantyn Kravchenko / Shutterstock.com; Ben Cooper / Science Faction / Getty Images
A Preview of Calculus
CALCULUS IS FUNDAMENTALLY DIFFERENT from the mathematics that you have studied previously:
calculus is less static and more dynamic. It is concerned with change and motion; it deals with quantities that approach other quantities. For that reason it may be useful to have an overview of calculus
before beginning your study of the subject. Here we give a preview of some of the main ideas of
calculus and show how their foundations are built upon the concept of a limit.
1
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2
A PREVIEW OF CALCULUS
What Is Calculus?
The world around us is continually changing — populations increase, a cup of coffee
cools, a stone falls, chemicals react with one another, currency values fluctuate, and
so on. We would like to be able to analyze quantities or processes that are undergoing
continuous change. For example, if a stone falls 10 feet each second we could easily
tell how fast it is falling at any time, but this is not what happens — the stone falls faster
and faster, its speed changing at each instant. In studying calculus, we will learn how
to model (or describe) such instantaneously changing processes and how to find the
cumulative effect of these changes.
Calculus builds on what you have learned in algebra and analytic geometry but
advances these ideas spectacularly. Its uses extend to nearly every field of human activity. You will encounter numerous applications of calculus throughout this book.
At its core, calculus revolves around two key problems involving the graphs of functions — the area problem and the tangent problem — and an unexpected relationship
between them. Solving these problems is useful because the area under the graph of a
function and the tangent to the graph of a function have many important interpretations
in a variety of contexts.
The Area Problem
A¡
A∞
A™
The origins of calculus go back at least 2500 years to the ancient Greeks, who found
areas using the “method of exhaustion.” They knew how to find the area A of any polygon by dividing it into triangles, as in Figure 1, and adding the areas of these triangles.
It is a much more difficult problem to find the area of a curved figure. The Greek
method of exhaustion was to inscribe polygons in the figure and circumscribe polygons
about the figure, and then let the number of sides of the polygons increase. Figure 2
illustrates this process for the special case of a circle with inscribed regular polygons.
A¢
A£
A=A¡+A™+A£+A¢+A∞
FIGURE 1
A£
A¢
A∞
Aß
A¶
!!!
A¡™
!!!
FIGURE 2
Let An be the area of the inscribed regular polygon of n sides. As n increases, it appears
that An gets closer and closer to the area of the circle. We say that the area A of the circle
is the limit of the areas of the inscribed polygons, and we write
y
A − lim An
n l`
y=ƒ
A
x
0
FIGURE 3
The area A of the region under
the graph of f
The Greeks themselves did not use limits explicitly. However, by indirect reasoning,
Eudoxus (fifth century bc) used exhaustion to prove the familiar formula for the area of
a circle: A − !r 2.
We will use a similar idea in Chapter 5 to find areas of regions of the type shown
in Figure 3. We approximate such an area by areas of rectangles as shown in Figure 4.
If we approximate the area A of the region under the graph of f by using n rectangles
R1 , R2 , . . . , Rn , then the approximate area is
An − R1 1 R2 1 c 1 Rn
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A PREVIEW OF CALCULUS
y
y
R¡
R™
R£
3
y
R¢
x
0
x
0
x
0
FIGURE 4 Approximating the area A using rectangles
Now imagine that we increase the number of rectangles (as the width of each one
decreases) and calculate A as the limit of these sums of areas of rectangles:
A − lim An
n l`
In Chapter 5 we will learn how to calculate such limits.
The area problem is the central problem in the branch of calculus called integral
calculus; it is important because the area under the graph of a function has different
interpretations depending on what the function represents. In fact, the techniques that
we develop for finding areas will also enable us to compute the volume of a solid, the
length of a curve, the force of water against a dam, the mass and center of mass of a rod,
the work done in pumping water out of a tank, and the amount of fuel needed to send a
rocket into orbit.
y
The Tangent Problem
L
y=ƒ
P
0
x
FIGURE 5
The tangent line at P
y
Consider the problem of trying to find an equation of the tangent line L to a curve with
equation y − f sxd at a given point P. (We will give a precise definition of a tangent line
in Chapter 2; for now you can think of it as the line that touches the curve at P and follows the direction of the curve at P, as in Figure 5.) Because the point P lies on the
tangent line, we can find the equation of L if we know its slope m. The problem is that
we need two points to compute the slope and we know only one point, P, on L. To get
around the problem we first find an approximation to m by taking a nearby point Q on
the curve and computing the slope m PQ of the secant line PQ.
Now imagine that Q moves along the curve toward P as in Figure 6. You can see that
the secant line PQ rotates and approaches the tangent line L as its limiting position. This
y
L
L
Q
Q
Q
P
P
0
y
L
x
0
P
x
0
x
FIGURE 6 The secant lines approach the tangent line as Q approaches P.
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4
A PREVIEW OF CALCULUS
y
means that the slope m PQ of the secant line becomes closer and closer to the slope m of
the tangent line. We write
L
Q { x, ƒ}
ƒ-f(a)
P { a, f(a)}
m − lim mPQ
QlP
and say that m is the limit of m PQ as Q approaches P along the curve.
Notice from Figure 7 that if P is the point sa, f sadd and Q is the point sx, f sxdd, then
x-a
a
0
FIGURE 7
The secant line PQ
x
x
mPQ −
f sxd 2 f sad
x2a
Because x approaches a as Q approaches P, an equivalent expression for the slope of
the tangent line is
f sxd 2 f sad
xla
x2a
m − lim
In Chapter 3 we will learn rules for calculating such limits.
The tangent problem has given rise to the branch of calculus called differential
calculus; it is important because the slope of a tangent to the graph of a function can
have different interpretations depending on the context. For instance, solving the tangent problem allows us to find the instantaneous speed of a falling stone, the rate of
change of a chemical reaction, or the direction of the forces on a hanging chain.
A Relationship between the Area and Tangent Problems
The area and tangent problems seem to be very different problems but, surprisingly,
the problems are closely related — in fact, they are so closely related that solving one
of them leads to a solution of the other. The relationship between these two problems
is introduced in Chapter 5; it is the central discovery in calculus and is appropriately
named the Fundamental Theorem of Calculus. Perhaps most importantly, the Fundamental Theorem vastly simplifies the solution of the area problem, making it possible
to find areas without having to approximate by rectangles and evaluate the associated
limits.
Isaac Newton (1642 –1727) and Gottfried Leibniz (1646 –1716) are credited with
the invention of calculus because they were the first to recognize the importance of the
Fundamental Theorem of Calculus and to utilize it as a tool for solving real-world problems. In studying calculus you will discover these powerful results for yourself.
Summary
We have seen that the concept of a limit arises in finding the area of a region and in finding the slope of a tangent line to a curve. It is this basic idea of a limit that sets calculus
apart from other areas of mathematics. In fact, we could define calculus as the part of
mathematics that deals with limits. We have mentioned that areas under curves and
slopes of tangent lines to curves have many different interpretations in a variety of contexts. Finally, we have discussed that the area and tangent problems are closely related.
After Isaac Newton invented his version of calculus, he used it to explain the motion
of the planets around the sun, giving a definitive answer to a centuries-long quest for a
description of our solar system. Today calculus is applied in a great variety of contexts,
such as determining the orbits of satellites and spacecraft, predicting population sizes,
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A PREVIEW OF CALCULUS
5
forecasting weather, measuring cardiac output, and gauging the efficiency of an economic market.
In order to convey a sense of the power and versatility of calculus, we conclude with
a list of some of the questions that you will be able to answer using calculus.
1. How can we design a roller coaster for a safe and smooth ride?
(See the Applied Project following Section 3.1.)
2. How far away from an airport should a pilot start descent?
(See the Applied Project following Section 3.4.)
3. How can we explain the fact that the angle of elevation from an observer up to the
highest point in a rainbow is always 42°?
(See the Applied Project following Section 4.1.)
4. How can we estimate the amount of work that was required to build the Great
Pyramid of Khufu in ancient Egypt?
(See Exercise 36 in Section 6.4.)
5. With what speed must a projectile be launched with so that it escapes the earth’s
gravitation pull?
(See Exercise 77 in Section 7.8.)
6. How can we explain the changes in the thickness of sea ice over time and why
cracks in the ice tend to “heal”?
(See Exercise 56 in Section 9.3.)
7. Does a ball thrown upward take longer to reach its maximum height or to fall back
down to its original height?
(See the Applied Project following Section 9.5.)
8. How can we fit curves together to design shapes to represent letters on a laser
printer?
(See the Applied Project following Section 10.2.)
9. How can we explain the fact that planets and satellites move in elliptical orbits?
(See the Applied Project following Section 13.4.)
10. How can we distribute water flow among turbines at a hydroelectric station so as
to maximize the total energy production?
(See the Applied Project following Section 14.8.)
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The electrical power produced by a wind turbine can be estimated by a mathematical function that incorporates several factors. We will
explore this function in Exercise 1.2.25 and determine the expected power output of a particular turbine for various wind speeds.
chaiviewfinder / Shutterstock.com
1
Functions and Models
THE FUNDAMENTAL OBJECTS THAT WE deal with in calculus are functions. This chapter prepares
the way for calculus by discussing the basic ideas concerning functions, their graphs, and ways of
transforming and combining them. We stress that a function can be represented in different ways:
by an equation, in a table, by a graph, or in words. We look at the main types of functions that
occur in calculus and describe the process of using these functions as mathematical models of realworld phenomena.
7
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
8
CHAPTER 1
Functions and Models
1.1 Four Ways to Represent a Function
■ Functions
Functions arise whenever one quantity depends on another. Consider the following four
situations.
A. The area A of a circle depends on the radius r of the circle. The rule that connects r
and A is given by the equation A − !r 2. With each positive number r there is associated one value of A, and we say that A is a function of r.
Table 1 World Population
Year
Population
(millions)
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
1650
1750
1860
2070
2300
2560
3040
3710
4450
5280
6080
6870
B. The human population of the world P depends on the time t. Table 1 gives estimates
of the world population P at time t, for certain years. For instance,
P < 2,560,000,000
when t − 1950
For each value of the time t there is a corresponding value of P, and we say that P is
a function of t.
C. The cost C of mailing an envelope depends on its weight w. Although there is no
simple formula that connects w and C, the post office has a rule for determining C
when w is known.
D. The vertical acceleration a of the ground as measured by a seismograph during an
earthquake is a function of the elapsed time t. Figure 1 shows a graph generated by
seismic activity during the Northridge earthquake that shook Los Angeles in 1994.
For a given value of t, the graph provides a corresponding value of a.
a
{cm/s@}
100
50
5
FIGURE 1
Vertical ground acceleration
during the Northridge earthquake
10
15
20
25
30
t (seconds)
_50
Calif. Dept. of Mines and Geology
Each of these examples describes a rule whereby, given a number (r in Example A),
another number (A) is assigned. In each case we say that the second number is a function
of the first number. If f represents the rule that connects A to r in Example A, then we
express this in function notation as A − f srd.
A function f is a rule that assigns to each element x in a set D exactly one element, called f sxd, in a set E.
We usually consider functions for which the sets D and E are sets of real numbers.
The set D is called the domain of the function. The number f sxd is the value of f at x
and is read “ f of x.” The range of f is the set of all possible values of f sxd as x varies
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.1
x
(input)
ƒ
(output)
f
FIGURE 2
Machine diagram for a function f
x
ƒ
a
f(a)
f
D
9
Four Ways to Represent a Function
throughout the domain. A symbol that represents an arbitrary number in the domain of a
function f is called an independent variable. A symbol that represents a number in the
range of f is called a dependent variable. In Example A, for instance, r is the independent variable and A is the dependent variable.
It’s helpful to think of a function as a machine (see Figure 2). If x is in the domain of
the function f, then when x enters the machine, it’s accepted as an input and the machine
produces an output f sxd according to the rule of the function. So we can think of the
domain as the set of all possible inputs and the range as the set of all possible outputs.
The preprogrammed functions in a calculator are good examples of a function as a
machine. For example, if you input a number and press the squaring key, the calculator
displays the output, the square of the input.
Another way to picture a function is by an arrow diagram as in Figure 3. Each arrow
connects an element of D to an element of E. The arrow indicates that f sxd is associated
with x, f sad is associated with a, and so on.
Perhaps the most useful method for visualizing a function is its graph. If f is a function with domain D, then its graph is the set of ordered pairs
|
hsx, f sxdd x [ Dj
E
(Notice that these are input-output pairs.) In other words, the graph of f consists of all
points sx, yd in the coordinate plane such that y − f sxd and x is in the domain of f.
The graph of a function f gives us a useful picture of the behavior or “life history” of
a function. Since the y-coordinate of any point sx, yd on the graph is y − f sxd, we can
read the value of f sxd from the graph as being the height of the graph above the point x.
(See Figure 4.) The graph of f also allows us to picture the domain of f on the x-axis and
its range on the y-axis as in Figure 5.
FIGURE 3
Arrow diagram for f
y y
f (1)f(1)
0 0
y y
{ x, ƒ
{ x, ƒ
} }
1 1
f (2)f(2)
2 2
ƒƒ
x x
x x
FIGURE 4
range
range
0 0
! ƒ(x)
y !y ƒ(x)
domain
domain
x x
FIGURE 5
y
EXAMPLE 1 The graph of a function f is shown in Figure 6.
(a) Find the values of f s1d and f s5d.
(b) What are the domain and range of f ?
1
SOLUTION
(a) We see from Figure 6 that the point s1, 3d lies on the graph of f, so the value of f
at 1 is f s1d − 3. (In other words, the point on the graph that lies above x − 1 is 3 units
above the x-axis.)
When x − 5, the graph lies about 0.7 units below the x-axis, so we estimate that
f s5d < 20.7.
(b) We see that f sxd is defined when 0 < x < 7, so the domain of f is the closed
interval f0, 7g. Notice that f takes on all values from 22 to 4, so the range of f is
0
1
x
FIGURE 6
The notation for intervals is given in
Appendix A.
|
hy 22 < y < 4j − f22, 4g
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
n
10
CHAPTER 1
Functions and Models
In calculus, the most common method of defining a function is by an algebraic equation. For example, the equation y − 2x 2 1 defines y as a function of x. We can express
this in function notation as fsxd − 2x 2 1.
y
EXAMPLE 2 Sketch the graph and find the domain and range of each function.
(a) fsxd − 2x 2 1
(b) tsxd − x 2
y=2x-1
0
-1
x
1
2
FIGURE 7
y
(2, 4)
y=≈
(_1, 1)
|
1
0
1
SOLUTION
(a) The equation of the graph is y − 2x 2 1, and we recognize this as being the
equation of a line with slope 2 and y-intercept 21. (Recall the slope-intercept form of
the equation of a line: y − mx 1 b. See Appendix B.) This enables us to sketch a
portion of the graph of f in Figure 7. The expression 2x 2 1 is defined for all real
numbers, so the domain of f is the set of all real numbers, which we denote by R. The
graph shows that the range is also R.
(b) Since ts2d − 2 2 − 4 and ts21d − s21d2 − 1, we could plot the points s2, 4d and
s21, 1d, together with a few other points on the graph, and join them to produce the
graph (Figure 8). The equation of the graph is y − x 2, which represents a parabola (see
Appendix C). The domain of t is R. The range of t consists of all values of tsxd, that is,
all numbers of the form x 2. But x 2 > 0 for all numbers x and any positive number y is a
square. So the range of t is hy y > 0j − f0, `d. This can also be seen from Figure 8.
x
n
f sa 1 hd 2 f sad
EXAMPLE 3 If f sxd − 2x 2 2 5x 1 1 and h ± 0, evaluate
.
h
SOLUTION We first evaluate f sa 1 hd by replacing x by a 1 h in the expression for f sxd:
FIGURE 8
f sa 1 hd − 2sa 1 hd2 2 5sa 1 hd 1 1
− 2sa 2 1 2ah 1 h 2 d 2 5sa 1 hd 1 1
− 2a 2 1 4ah 1 2h 2 2 5a 2 5h 1 1
The expression
Then we substitute into the given expression and simplify:
f sa 1 hd 2 f sad
s2a 2 1 4ah 1 2h 2 2 5a 2 5h 1 1d 2 s2a 2 2 5a 1 1d
−
h
h
f sa 1 hd 2 f sad
h
in Example 3 is called a difference
quotient and occurs frequently in
calculus. As we will see in Chapter 2,
it represents the average rate of
change of f sxd between x − a and
x − a 1 h.
2a 2 1 4ah 1 2h 2 2 5a 2 5h 1 1 2 2a 2 1 5a 2 1
h
2
4ah 1 2h 2 5h
−
− 4a 1 2h 2 5
h
−
n
■ Representations of Functions
We consider four different ways to represent a function:
●
verbally
(by a description in words)
●
numerically
(by a table of values)
●
visually
(by a graph)
●
algebraically
(by an explicit formula)
If a single function can be represented in all four ways, it’s often useful to go from one
representation to another to gain additional insight into the function. (In Example 2, for
instance, we started with algebraic formulas and then obtained graphs.) But certain functions are described more naturally by one method than by another. With this in mind, let’s
reexamine the four situations that we considered at the beginning of this section.
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SECTION 1.1
Table 2 World Population
t
(years
since 1900)
Population
(millions)
0
10
20
30
40
50
60
70
80
90
100
110
1650
1750
1860
2070
2300
2560
3040
3710
4450
5280
6080
6870
A. The most useful representation of the area of a circle as a function of its radius is
probably the algebraic formula A − !r 2 or, in function notation, Asrd − !r 2. It is
also possible to compile a table of values or sketch a graph (half a parabola). Because
a circle has to have a positive radius, the domain is hr r . 0j − s0, `d and the range
is also s0, `d.
B. We are given a description of the function in words: Pstd is the human population of
the world at time t. Let’s measure t so that t − 0 corresponds to the year 1900. Table 2
provides a convenient representation of this function. If we plot the ordered pairs in
the table, we get the graph (called a scatter plot) in Figure 9. It too is a useful representation; the graph allows us to absorb all the data at once. What about a formula?
Of course, it’s impossible to devise an explicit formula that gives the exact human
population Pstd at any time t. But it is possible to find an expression for a function that
approximates Pstd. In fact, using methods explained in Section 1.4, we obtain an
approximation for the population P:
|
Pstd < f std − s1.43653 3 10 9 d ∙ s1.01395d t
Figure 10 shows that it is a reasonably good “fit.” The function f is called a mathematical model for population growth. In other words, it is a function with an explicit
formula that approximates the behavior of our given function. We will see, however,
that the ideas of calculus can be applied to a table of values; an explicit formula is not
necessary.
P
P
5x10'
5x10'
0
20
40
11
Four Ways to Represent a Function
60
80
Years since 1900
FIGURE 9
100
120
t
0
20
40
60
80
Years since 1900
100
120
t
FIGURE 10
A function defined by a table of
values is called a tabular function.
Table 3
w (ounces)
Cswd (dollars)
0,w<1
1.00
1,w<2
2,w<3
3,w<4
4,w<5
∙
∙
∙
1.15
1.30
1.45
1.60
∙
∙
∙
The function P is typical of the functions that arise whenever we attempt to apply
calculus to the real world. We start with a verbal description of a function. Then we
may be able to construct a table of values of the function, perhaps from instrument
readings in a scientific experiment. Even though we don’t have complete knowledge
of the values of the function, we will see throughout the book that it is still possible
to perform the operations of calculus on such a function.
C. Again, the function is described in words: Let Cswd be the cost of mailing a large
envelope with weight w. The rule that the US Postal Service used as of 2019 is as
follows: The cost is 1 dollar for up to 1 oz, plus 15 cents for each additional ounce (or
less) up to 13 oz. A table of values is the most convenient representation for this function (see Table 3), though it is possible to sketch a graph (see Example 10).
D. The graph shown in Figure 1 is the most natural representation of the vertical acceleration function astd. It’s true that a table of values could be compiled, and it is
even possible to devise an approximate formula. But everything a geologist needs to
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12
CHAPTER 1
Functions and Models
know— amplitudes and patterns — can be seen easily from the graph. (The same is
true for the patterns seen in electrocardiograms of heart patients and polygraphs for
lie-detection.)
In the next example we sketch the graph of a function that is defined verbally.
EXAMPLE 4 When you turn on a hot-water faucet that is connected to a hot-water
tank, the temperature T of the water depends on how long the water has been running.
Draw a rough graph of T as a function of the time t that has elapsed since the faucet
was turned on.
T
t
0
FIGURE 11
SOLUTION The initial temperature of the running water is close to room temperature
because the water has been sitting in the pipes. When the water from the hot-water tank
starts flowing from the faucet, T increases quickly. In the next phase, T is constant at
the temperature of the heated water in the tank. When the tank is drained, T decreases
to the temperature of the water supply. This enables us to make the rough sketch of T
as a function of t shown in Figure 11.
n
In the following example we start with a verbal description of a function in a physical
situation and obtain an explicit algebraic formula. The ability to do this is a useful skill
in solving calculus problems that ask for the maximum or minimum values of quantities.
EXAMPLE 5 A rectangular storage container with an open top has a volume of 10 m3.
The length of its base is twice its width. Material for the base costs $10 per square
meter; material for the sides costs $6 per square meter. Express the cost of materials as
a function of the width of the base.
h
w
2w
FIGURE 12
SOLUTION We draw a diagram as in Figure 12 and introduce notation by letting w and
2w be the width and length of the base, respectively, and h be the height.
The area of the base is s2wdw − 2w 2, so the cost, in dollars, of the material for the
base is 10s2w 2 d. Two of the sides have area wh and the other two have area 2wh, so the
cost of the material for the sides is 6f2swhd 1 2s2whdg. The total cost is therefore
C − 10s2w 2 d 1 6f2swhd 1 2s2whdg − 20 w 2 1 36 wh
To express C as a function of w alone, we need to eliminate h and we do so by using
the fact that the volume is 10 m3. Thus
w s2wdh − 10
which gives
PS In setting up applied functions as in
Example 5, it may be useful to review the
principles of problem solving at the end of
this chapter, particularly Step 1: Understand the Problem.
h−
10
5
2 −
2w
w2
Substituting this into the expression for C, we have
S D
C − 20w 2 1 36w
5
w2
− 20w 2 1
180
w
Therefore the equation
Cswd − 20w 2 1
expresses C as a function of w.
180
w
w.0
n
In the next example we find the domain of a function that is defined algebraically.
If a function is given by a formula and the domain is not stated explicitly, we use the
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SECTION 1.1
Four Ways to Represent a Function
13
following domain convention: the domain of the function is the set of all inputs for
which the formula makes sense and gives a real-number output.
EXAMPLE 6 Find the domain of each function.
(b) tsxd −
(a) f sxd − sx 1 2
1
x 2x
2
SOLUTION
(a) Because the square root of a negative number is not defined (as a real number),
the domain of f consists of all values of x such that x 1 2 > 0. This is equivalent to
x > 22, so the domain is the interval f22, `d.
(b) Since
1
1
tsxd − 2
−
x 2x
xsx 2 1d
and division by 0 is not allowed, we see that tsxd is not defined when x − 0 or x − 1.
So the domain of t is
hx x ± 0, x ± 1j
|
which could also be written in interval notation as
s2`, 0d ø s0, 1d ø s1, `d
n
■ Which Rules Define Functions?
y
0
x=a
Not every equation defines a function. The equation y − x 2 defines y as a function of x
because the equation determines exactly one value of y for each value of x. However, the
equation y 2 − x does not define y as a function of x because some input values x correspond to more than one output y; for instance, for the input x − 4 the equation gives the
outputs y − 2 and y − !2.
Similarly, not every table defines a function. Table 3 defined C as a function of w — each
package weight w corresponds to exactly one mailing cost. On the other hand, Table 4 does
not define y as a function of x because some input values x in the table correspond to more
than one output y; for instance, the input x − 5 gives the outputs y − 7 and y − 8.
(a, b)
Table 4
x
a
(a) This curve represents a function.
y
(a, c)
x=a
a
(b) This curve doesn’t represent
a function.
FIGURE 13
2
4
5
5
6
y
3
6
7
8
9
What about curves drawn in the xy-plane? Which curves are graphs of functions? The
following test gives an answer.
The Vertical Line Test A curve in the xy-plane is the graph of a function of x if
and only if no vertical line intersects the curve more than once.
(a, b)
0
x
x
The reason for the truth of the Vertical Line Test can be seen in Figure 13. If each
vertical line x − a intersects a curve only once, at sa, bd, then exactly one function value
is defined by f sad − b. But if a line x − a intersects the curve twice, at sa, bd and sa, cd,
then the curve can’t represent a function because a function can’t assign two different
values to a.
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14
CHAPTER 1
Functions and Models
For example, the parabola x − y 2 2 2 shown in Figure 14(a) is not the graph of a
function of x because, as you can see, there are vertical lines that intersect the parabola
twice. The parabola, however, does contain the graphs of two functions of x. Notice
that the equation x − y 2 2 2 implies y 2 − x 1 2, so y − 6sx 1 2 . Thus the upper
and lower halves of the parabola are the graphs of the functions f sxd − s x 1 2 [from
Example 6(a)] and tsxd − 2s x 1 2 . [See Figures 14(b) and (c).]
y
(_2, 0)
FIGURE 14
0
y
x
_2 0
y
_2
x
(b) y=œ„„„„
x+2
(a) x=¥-2
0
x
(c) y=_ œ„„„„
x+2
We observe that if we reverse the roles of x and y, then the equation x − hsyd − y 2 2 2
does define x as a function of y (with y as the independent variable and x as the dependent variable). The graph of the function h is the parabola in Figure 14(a).
■ Piecewise Defined Functions
The functions in the following four examples are defined by different formulas in different parts of their domains. Such functions are called piecewise defined functions.
EXAMPLE 7 A function f is defined by
f sxd −
H
1 2 x if x < 21
x2
if x . 21
Evaluate f s22d, f s21d, and f s0d and sketch the graph.
SOLUTION Remember that a function is a rule. For this particular function the rule is
the following: First look at the value of the input x. If it happens that x < 21, then the
value of f sxd is 1 2 x. On the other hand, if x . 21, then the value of f sxd is x 2. Note
that even though two different formulas are used, f is one function, not two.
Since 22 < 21, we have f s22d − 1 2 s22d − 3.
Since 21 < 21, we have f s21d − 1 2 s21d − 2.
y
Since 0 . 21, we have f s0d − 0 2 − 0.
1
_1
0
1
x
FIGURE 15
How do we draw the graph of f ? We observe that if x < 21, then f sxd − 1 2 x,
so the part of the graph of f that lies to the left of the vertical line x − 21 must
coincide with the line y − 1 2 x, which has slope 21 and y-intercept 1. If x . 21,
then f sxd − x 2, so the part of the graph of f that lies to the right of the line x − 21
must coincide with the graph of y − x 2, which is a parabola. This enables us to sketch
the graph in Figure 15. The solid dot indicates that the point s21, 2d is included on the
graph; the open dot indicates that the point s21, 1d is excluded from the graph.
n
The next example of a piecewise defined function is the absolute value function.
Recall that the absolute value of a number a, denoted by a , is the distance from a to 0
on the real number line. Distances are always positive or 0, so we have
| |
For a more extensive review of
absolute values, see Appendix A.
|a| > 0
for every number a
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SECTION 1.1
Four Ways to Represent a Function
15
For example,
| 3 | − 3 | 23 | − 3 | 0 | − 0 | s2 2 1 | − s2 2 1 | 3 2 ! | − ! 2 3
In general, we have
| a | − a if a > 0
| a | − 2a if a , 0
(Remember that if a is negative, then 2a is positive.)
EXAMPLE 8 Sketch the graph of the absolute value function f sxd − | x |.
y
y=| x |
SOLUTION From the preceding discussion we know that
H
x
if x > 0
| x | − 2x if x , 0
0
x
Using the same method as in Example 7, we see that the graph of f coincides with the
line y − x to the right of the y-axis and coincides with the line y − 2x to the left of the
y-axis (see Figure 16).
n
FIGURE 16
y
EXAMPLE 9 Find a formula for the function f graphed in Figure 17.
1
SOLUTION The line through s0, 0d and s1, 1d has slope m − 1 and y-intercept b − 0,
so its equation is y − x. Thus, for the part of the graph of f that joins s0, 0d to s1, 1d,
we have
f sxd − x
if 0 < x < 1
0
x
1
The line through s1, 1d and s2, 0d has slope m − 21, so its point-slope form is
FIGURE 17
y 2 0 − s21dsx 2 2d
The point-slope form of the equation
of a line is y 2 y1 − msx 2 x 1 d . See
Appendix B.
So we have
f sxd − 2 2 x
or
y−22x
if 1 , x < 2
We also see that the graph of f coincides with the x-axis for x . 2. Putting this information together, we have the following three-piece formula for f :
H
x
if 0 < x < 1
f sxd − 2 2 x if 1 , x < 2
0
if x . 2
C
1.50
EXAMPLE 10 In Example C at the beginning of this section we considered the cost
Cswd of mailing a large envelope with weight w. In effect, this is a piecewise defined
function because, from Table 3, we have
1.00
0.50
0
n
Cswd −
1
FIGURE 18
2
3
4
5
w
1.00
1.15
1.30
1.45
∙
∙
∙
if 0 , w < 1
if 1 , w < 2
if 2 , w < 3
if 3 , w < 4
The graph is shown in Figure 18.
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n
16
CHAPTER 1
Functions and Models
Looking at Figure 18, you can see why a function like the one in Example 10 is called
a step function.
■ Even and Odd Functions
y
f(_x)
If a function f satisfies f s2xd − f sxd for every number x in its domain, then f is called
an even function. For instance, the function f sxd − x 2 is even because
ƒ
_x
0
x
x
f s2xd − s2xd2 − x 2 − f sxd
The geometric significance of an even function is that its graph is symmetric with respect
to the y-axis (see Figure 19). This means that if we have plotted the graph of f for x > 0,
we obtain the entire graph simply by reflecting this portion about the y-axis.
If f satisfies f s2xd − 2f sxd for every number x in its domain, then f is called an odd
function. For example, the function f sxd − x 3 is odd because
FIGURE 19
An even function
y
_x
0
f s2xd − s2xd3 − 2x 3 − 2f sxd
ƒ
x
x
The graph of an odd function is symmetric about the origin (see Figure 20). If we already
have the graph of f for x > 0, we can obtain the entire graph by rotating this portion
through 1808 about the origin.
EXAMPLE 11 Determine whether each of the following functions is even, odd, or
neither even nor odd.
(a) f sxd − x 5 1 x
(b) tsxd − 1 2 x 4
(c) hsxd − 2x 2 x 2
FIGURE 20
SOLUTION
(a)
An odd function
f s2xd − s2xd5 1 s2xd − s21d5x 5 1 s2xd
− 2x 5 2 x − 2sx 5 1 xd
− 2f sxd
Therefore f is an odd function.
ts2xd − 1 2 s2xd4 − 1 2 x 4 − tsxd
(b)
So t is even.
hs2xd − 2s2xd 2 s2xd2 − 22x 2 x 2
(c)
Since hs2xd ± hsxd and hs2xd ± 2hsxd, we conclude that h is neither even nor odd.
n
The graphs of the functions in Example 11 are shown in Figure 21. Notice that the
graph of h is symmetric neither about the y-axis nor about the origin.
1
_1
y
y
y
1
f
1
g
1
x
h
1
x
1
x
_1
FIGURE 21
(a)
( b)
(c)
■ Increasing and Decreasing Functions
The graph shown in Figure 22 rises from A to B, falls from B to C, and rises again from C
to D. The function f is said to be increasing on the interval fa, bg, decreasing on fb, cg,
and increasing again on fc, dg. Notice that if x 1 and x 2 are any two numbers between
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.1
Four Ways to Represent a Function
17
a and b with x 1 , x 2, then f sx 1 d , f sx 2 d. We use this as the defining property of an
increasing function.
B
y
D
y=ƒ
f(x¡)
A
0
FIGURE 22
a x¡
C
f(x™)
x™
b
c
d
x
A function f is called increasing on an interval I if
f sx 1 d , f sx 2 d
y
y=≈
It is called decreasing on I if
f sx 1 d . f sx 2 d
whenever x 1 , x 2 in I
In the definition of an increasing function it is important to realize that the inequality
f sx 1 d , f sx 2 d must be satisfied for every pair of numbers x 1 and x 2 in I with x 1 , x 2.
You can see from Figure 23 that the function f sxd − x 2 is decreasing on the interval
s2`, 0g and increasing on the interval f0, `d.
x
0
whenever x 1 , x 2 in I
FIGURE 23
1.1 Exercises
1. If f sxd − x 1 s2 2 x and tsud − u 1 s2 2 u , is it true
that f − t ?
2. If
(a) State the values of f s24d and ts3d.
(b) Which is larger, f s23d or ts!3d ?
x2 2 x
f sxd −
x21
and
tsxd − x
is it true that f − t ?
3. The graph of a function t is given.
(a) State the values of ts!2d, ts0d, ts2d, and ts3d.
(b) For what value(s) of x is tsxd − 3 ?
(c) For what value(s) of x is tsxd ⩽ 3 ?
(d) State the domain and range of t.
(e) On what interval(s) is t increasing?
y
3
_3
4. The graphs of f and t are given.
0
g
3
(c) For what values of x is f sxd − tsxd ?
(d) On what interval(s) is f sxd ⩽ tsxd ?
(e) State the solution of the equation f sxd − 21.
(f ) On what interval(s) is t decreasing?
(g) State the domain and range of f.
(h) State the domain and range of t.
y
f
g
2
0
2
x
x
5. Figure 1 was recorded by an instrument operated by the
California Department of Mines and Geology at the
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18
CHAPTER 1
Functions and Models
University Hospital of the University of Southern California
in Los Angeles. Use it to estimate the range of the vertical
ground acceleration function at USC during the Northridge
earthquake.
(c) The years when the temperature was smallest and largest
(d) The range of T
T (•C)
6. In this section we discussed examples of ordinary, everyday
functions: population is a function of time, postage cost is a
function of package weight, water temperature is a function
of time. Give three other examples of functions from everyday life that are described verbally. What can you say about
the domain and range of each of your functions? If possible,
sketch a rough graph of each function.
14
13
7–14 Determine whether the equation or table defines y as a
function of x.
9. x 1 sy 2 3d − 5
10. 2xy 1 5y − 4
11. s y 1 3d3 1 1 − 2x
12. 2x 2 y − 0
13.
14.
2
2
x
y
Height (in) Shoe size
72
60
60
63
70
2
| |
12
8
7
9
10
x
y
Year Tuition cost ($)
2016
2017
2018
2019
2020
10,900
11,000
11,200
11,200
11,300
15–18 Determine whether the curve is the graph of a function
of x. If it is, state the domain and range of the function.
15.
17.
yy y
16.
yy y
11 1
11 1
00 0 11 1 xx x
00 0 11 1 xx x
yy y
yy y
18.
11 1
11 1
00 0 11 1 xx x
0 0 11 1 x x
19. Shown is a graph of the global average temperature T during
the 20th century. Estimate the following.
(a) The global average temperature in 1950
(b) The year when the average temperature was 14.2°C
2000 t
1950
Source: Adapted from Globe and Mail [Toronto], 5 Dec. 2009. Print.
20. Trees grow faster and form wider rings in warm years and
grow more slowly and form narrower rings in cooler years.
The figure shows ring widths of a Siberian pine from 1500
to 2000.
(a) What is the range of the ring width function?
(b) What does the graph tend to say about the temperature of
the earth? Does the graph reflect the volcanic eruptions of
the mid-19th century?
R
Ring width (mm)
8. 3x 2 2 2y − 5
7. 3x 2 5y − 7
1900
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1500
1600
1700
1800
1900
2000 t
Year
Source: Adapted from G. Jacoby et al., “Mongolian Tree Rings
and 20th-Century Warming,” Science 273 (1996): 771–73.
21. You put some ice cubes in a glass, fill the glass with cold
water, and then let the glass sit on a table. Describe how the
temperature of the water changes as time passes. Then sketch
a rough graph of the temperature of the water as a function of
the elapsed time.
22. You place a frozen pie in an oven and bake it for an hour.
Then you take it out and let it cool. Describe how the temperature of the pie changes as time passes. Then sketch a rough
graph of the temperature of the pie as a function of time.
23. The graph shows the power consumption for a day in September in San Francisco. (P is measured in megawatts; t is measured in hours starting at midnight.)
(a) What was the power consumption at 6 am? At 6 pm?
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SECTION 1.1
(b) When was the power consumption the lowest? When was
it the highest? Do these times seem reasonable?
P
800
600
400
3
6
9
12
15
18
21
t
Pacific Gas & Electric
24. Three runners compete in a 100-meter race. The graph
depicts the distance run as a function of time for each
runner. Describe in words what the graph tells you about
this race. Who won the race? Did each runner finish the
race?
y
100
0
31. Temperature readings T (in °F) were recorded every two
hours from midnight to 2:00 pm in Atlanta on a day in June.
The time t was measured in hours from midnight.
t
0
2
4
6
8
10
12
14
T
74
69
68
66
70
78
82
86
(a) Use the readings to sketch a rough graph of T as a
function of t.
(b) Use your graph to estimate the temperature at 9:00 am.
200
0
19
Four Ways to Represent a Function
A
B
C
20
25. Sketch a rough graph of the outdoor temperature as a function
of time during a typical spring day.
26. Sketch a rough graph of the number of hours of daylight as a
function of the time of year.
27. Sketch a rough graph of the amount of a particular brand of
coffee sold by a store as a function of the price of the coffee.
28. Sketch a rough graph of the market value of a new car as a
function of time for a period of 20 years. Assume the car is
well maintained.
29. A homeowner mows the lawn every Wednesday afternoon.
Sketch a rough graph of the height of the grass as a function
of time over the course of a four-week period.
30. An airplane takes off from an airport and lands an hour later
at another airport, 400 miles away. If t represents the time in
minutes since the plane has left the terminal building, let xstd
be the horizontal distance traveled and ystd be the altitude of
the plane.
(a) Sketch a possible graph of xstd.
(b) Sketch a possible graph of ystd.
(c) Sketch a possible graph of the ground speed.
(d) Sketch a possible graph of the vertical velocity.
32. Researchers measured the blood alcohol concentration (BAC)
of eight adult male subjects after rapid consumption of 30 mL
of ethanol (corresponding to two standard alcoholic drinks).
The table shows the data they obtained by averaging the BAC
(in gydL) of the eight men.
(a) Use the readings to sketch a graph of the BAC as a
function of t.
(b) Use your graph to describe how the effect of alcohol
varies with time.
t (hours)
BAC
t (hours)
BAC
0
0.2
0.5
0.75
1.0
1.25
1.5
0
0.025
0.041
0.040
0.033
0.029
0.024
1.75
2.0
2.25
2.5
3.0
3.5
4.0
0.022
0.018
0.015
0.012
0.007
0.003
0.001
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of
Ethanol after Oral Administration in the Fasting State,” Journal of
Pharmacokinetics and Biopharmaceutics 5 (1977): 207–24.
33. If f sxd − 3x 2 2 x 1 2, find f s2d, f s22d, f sad, f s2ad,
f sa 1 1d, 2 f sad, f s2ad, f sa 2 d, [ f sad] 2, and f sa 1 hd.
34. If tsxd −
x
, find ts0d, ts3d, 5tsad, 12 ts4ad, tsa 2 d,
sx 1 1
ftsad! 2, tsa 1 hd, and tsx 2 ad.
35–38 Evaluate the difference quotient for the given function.
Simplify your answer.
f s3 1 hd 2 f s3d
35. f sxd − 4 1 3x 2 x 2,
h
f sa 1 hd 2 f sad
h
36. f sxd − x 3,
37. f sxd −
1
,
x
f sxd 2 f sad
x2a
38. f sxd − sx 1 2,
f sxd 2 f s1d
x21
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20
CHAPTER 1
Functions and Models
39–46 Find the domain of the function.
39. f sxd −
x14
x2 2 9
40. f sxd −
63.
x2 1 1
x 1 4x 2 21
42. tstd − s3 2 t 2 s2 1 t
1
43. hsxd − 4
sx 2 2 5x
44. f sud −
45. Fs pd − s2 2 s p
46. hsxd − sx 2 4x 2 5
u11
1
11
u11
2
47. Find the domain and range and sketch the graph of the
function hsxd − s4 2 x 2 .
48. Find the domain and sketch the graph of the function
x2 2 4
x22
50. f sxd −
51. f sxd −
52. f sxd −
H
H
H
H
x 2 1 2 if x , 0
x
if x > 0
5
if x , 2
1
x
2
3
if
x>2
2
x
1
|
|
H| | || ||
x
1
x
65. A rectangle has perimeter 20 m. Express the area of the rectangle as a function of the length of one of its sides.
66. A rectangle has area 16 m2. Express the perimeter of the rectangle as a function of the length of one of its sides.
67. Express the area of an equilateral triangle as a function of the
length of a side.
69. An open rectangular box with volume 2 m3 has a square base.
Express the surface area of the box as a function of the length
of a side of the base.
20
x
55. tstd − 1 2 3t
1
65–70 Find a formula for the described function and state its domain.
21
if x < 1
7 2 2x if x . 1
| |
0
71. A box with an open top is to be constructed from a rectangular piece of cardboard with dimensions 12 in. by 20 in.
by cutting out equal squares of side x at each corner
and then folding up the sides as in the figure. Express the
volume V of the box as a function of x.
x 1 1 if x < 21
x2
if x . 21
53. f sxd − x 1 x
58. tsxd −
0
1
70. A right circular cylinder has volume 25 in3. Express the
radius of the cylinder as a function of the height.
12
53–58 Sketch the graph of the function.
57. f sxd −
1
68. A closed rectangular box with volume 8 ft3 has length twice the
width. Express the height of the box as a function of the width.
49–52 Evaluate f s23d, f s0d, and f s2d for the piecewise defined
function. Then sketch the graph of the function.
49. f sxd −
y
2
3
41. f std − s
2t 2 1
f sxd −
64.
y
|
|x|
56. f sxd −
54. f sxd − x 1 2
|
x
if x < 1
if x . 1
x
x
x
x
x
x
x
72. A Norman window has the shape of a rectangle surmounted
by a semicircle. If the perimeter of the window is 30 ft,
express the area A of the window as a function of the width x
of the window.
|| x | 2 1|
59–64 Find a formula for the function whose graph is the given
curve.
59. The line segment joining the points s1, 23d and s5, 7d
60. The line segment joining the points s25, 10d and s7, 210d
61. The bottom half of the parabola x 1 s y 2 1d 2 − 0
62. The top half of the circle x 2 1 s y 2 2d 2 − 4
x
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SECTION 1.2
73. In a certain state the maximum speed permitted on freeways
is 65 miyh and the minimum speed is 40 miyh. The fine for
violating these limits is $15 for every mile per hour above the
maximum speed or below the minimum speed. Express the
amount of the fine F as a function of the driving speed x and
graph Fsxd for 0 < x < 100.
Mathematical Models: A Catalog of Essential Functions
79–80 The graph of a function defined for x > 0 is given.
Complete the graph for x , 0 to make (a) an even function and
(b) an odd function.
y
79.
74. An electricity company charges its customers a base rate of $10
a month, plus 6 cents per kilowatt-hour (kWh) for the first
1200 kWh and 7 cents per kWh for all usage over 1200 kWh.
Express the monthly cost E as a function of the amount x of
electricity used. Then graph the function E for 0 < x < 2000.
75. In a certain country, income tax is assessed as follows. There
is no tax on income up to $10,000. Any income over $10,000
is taxed at a rate of 10%, up to an income of $20,000. Any
income over $20,000 is taxed at 15%.
(a) Sketch the graph of the tax rate R as a function of the
income I.
(b) How much tax is assessed on an income of $14,000?
On $26,000?
(c) Sketch the graph of the total assessed tax T as a function
of the income I.
76. (a) If the point s5, 3d is on the graph of an even function,
what other point must also be on the graph?
(b) If the point s5, 3d is on the graph of an odd function, what
other point must also be on the graph?
77–78 Graphs of f and t are shown. Decide whether each
function is even, odd, or neither. Explain your reasoning.
77.
y
78.
g
y
21
0
80.
x
y
0
x
81–86 Determine whether f is even, odd, or neither. You may
wish to use a graphing calculator or computer to check your
answer visually.
x2
x 11
81. f sxd −
x
x 11
82. f sxd −
83. f sxd −
x
x11
84. f sxd − x x
2
85. f sxd − 1 1 3x 2 2 x 4
4
| |
86. f sxd − 1 1 3x 3 2 x 5
f
f
x
g
x
87. If f and t are both even functions, is f 1 t even? If f and t
are both odd functions, is f 1 t odd? What if f is even and t
is odd? Justify your answers.
88. If f and t are both even functions, is the product ft even? If f
and t are both odd functions, is ft odd? What if f is even and
t is odd? Justify your answers.
1.2 Mathematical Models: A Catalog of Essential Functions
A mathematical model is a mathematical description (often by means of a function or
an equation) of a real-world phenomenon such as the size of a population, the demand
for a product, the speed of a falling object, the concentration of a product in a chemical
reaction, the life expectancy of a person at birth, or the cost of emissions reductions. The
purpose of the model is to understand the phenomenon and perhaps to make predictions
about future behavior.
Given a real-world problem, our first task in the mathematical modeling process is to
formulate a mathematical model by identifying and naming the independent and dependent variables and making assumptions that simplify the phenomenon enough to make
it mathematically tractable. We use our knowledge of the physical situation and our
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22
CHAPTER 1
Functions and Models
mathematical skills to obtain equations that relate the variables. In situations where there
is no physical law to guide us, we may need to collect data (either from the Internet or
a library or by conducting our own experiments) and examine the data in the form of a
table in order to discern patterns. From this numerical representation of a function we
may wish to obtain a graphical representation by plotting the data. The graph might even
suggest a suitable algebraic formula in some cases.
The second stage is to apply the mathematics that we know (such as the calculus that
will be developed throughout this book) to the mathematical model that we have formulated in order to derive mathematical conclusions. Then, in the third stage, we take those
mathematical conclusions and interpret them as information about the original realworld phenomenon by way of offering explanations or making predictions. The final step
is to test our predictions by checking against new real data. If the predictions don’t compare well with reality, we need to refine our model or formulate a new model and start
the cycle again. Figure 1 illustrates the process of mathematical modeling.
Real-world
problem
Formulate
Mathematical
model
Mathematical
conclusions
Solve
Interpret
Real-world
predictions
Test
FIGURE 1
A mathematical model is never a completely accurate representation of a physical
situation—it is an idealization. A good model simplifies reality enough to permit mathematical calculations but is accurate enough to provide valuable conclusions. It is important to realize the limitations of a model.
There are many different types of functions that can be used to model relationships
observed in the real world. In what follows, we discuss the behavior and graphs of some of
these functions and give examples of situations appropriately modeled by such functions.
The modeling process
■ Linear Models
The coordinate geometry of lines is
reviewed in Appendix B.
When we say that y is a linear function of x, we mean that the graph of the function is a
line, so we can use the slope-intercept form of the equation of a line to write a formula
for the function as
y − f sxd − mx 1 b
where m is the slope of the line and b is the y-intercept.
A characteristic feature of linear functions is that they change at a constant rate. For
instance, Figure 2 shows a graph of the linear function f sxd − 3x 2 2 and a table of
sample values. Notice that whenever x increases by 0.1, the value of f sxd increases
by 0.3. So f sxd increases three times as fast as x. This means that the slope of the graph
of y − 3x 2 2, namely 3, can be interpreted as the rate of change of y with respect to x.
y
y=3x-2
0
_2
FIGURE 2
1
x
x
f sxd − 3x 2 2
1.0
1.1
1.2
1.3
1.4
1.5
1.0
1.3
1.6
1.9
2.2
2.5
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SECTION 1.2
Mathematical Models: A Catalog of Essential Functions
23
EXAMPLE 1
(a) As dry air moves upward, it expands and cools. If the ground temperature is 20°C
and the temperature at a height of 1 km is 10°C, express the temperature T (in °C) as a
function of the height h (in kilometers), assuming that a linear model is appropriate.
(b) Draw the graph of the function in part (a). What does the slope represent?
(c) What is the temperature at a height of 2.5 km?
SOLUTION
(a) Because we are assuming that T is a linear function of h, we can write
T − mh 1 b
We are given that T − 20 when h − 0, so
20 − m ? 0 1 b − b
In other words, the y-intercept is b − 20.
We are also given that T − 10 when h − 1, so
T
20
10
10 − m ? 1 1 20
T=_10h+20
The slope of the line is therefore m − 10 2 20 − 210 and the required linear function is
T − 210h 1 20
0
1
h
3
(b) The graph is sketched in Figure 3. The slope is m − 210°Cykm, and this represents the rate of change of temperature with respect to height.
(c) At a height of h − 2.5 km, the temperature is
FIGURE 3
T − 210s2.5d 1 20 − 25°C
n
If there is no physical law or principle to help us formulate a model, we construct an
empirical model, which is based entirely on collected data. We seek a curve that “fits”
the data in the sense that it captures the basic trend of the data points.
Table 1
Year
CO2 level
(in ppm)
Year
CO2 level
(in ppm)
1980
1984
1988
1992
1996
338.7
344.4
351.5
356.3
362.4
2000
2004
2008
2012
2016
369.4
377.5
385.6
393.8
404.2
EXAMPLE 2 Table 1 lists the average carbon dioxide level in the atmosphere,
measured in parts per million at Mauna Loa Observatory from 1980 to 2016. Use the
data in Table 1 to find a model for the carbon dioxide level.
SOLUTION We use the data in Table 1 to make the scatter plot in Figure 4, where t
represents time (in years) and C represents the CO2 level (in parts per million, ppm).
C (ppm)
410
400
390
380
370
360
350
340
FIGURE 4
Scatter plot for the average CO2 level
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
t
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24
CHAPTER 1
Functions and Models
Notice that the data points appear to lie close to a straight line, so it’s natural to
choose a linear model in this case. But there are many possible lines that approximate
these data points, so which one should we use? One possibility is the line that passes
through the first and last data points. The slope of this line is
404.2 2 338.7
65.5
−
< 1.819
2016 2 1980
36
We write its equation as
C 2 338.7 − 1.819st 2 1980d
or
1
A computer or graphing calculator
finds the regression line by the
method of least squares, which is to
minimize the sum of the squares of
the vertical distances between the
data points and the line. The details
are explained in Exercise 14.7.61.
C − 1.819t 2 3262.92
Equation 1 gives one possible linear model for the carbon dioxide level; it is
graphed in Figure 5. Notice that our model gives values higher than most of the actual
CO2 levels. A better linear model is obtained by a procedure from statistics called
linear regression. Many graphing calculators and computer software applications can
determine the regression line for a set of data. One such calculator gives the slope
and y-intercept of the regression line for the data from Table 1 as
m − 1.78242
b − 23192.90
So our least squares model for the CO2 level is
2
C − 1.78242t 2 3192.90
In Figure 6 we graph the regression line as well as the data points. Comparing with
Figure 5, we see that the regression line gives a better fit.
C (ppm)
C (ppm)
410
410
400
400
390
390
380
380
370
370
360
360
350
350
340
340
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
t
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
FIGURE 5
FIGURE 6
Linear model through first and last data points
The regression line
t
n
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SECTION 1.2
Mathematical Models: A Catalog of Essential Functions
25
EXAMPLE 3 Use the linear model given by Equation 2 to estimate the average CO2
level for 1987 and to predict the level for the year 2025. According to this model, when
will the CO2 level exceed 440 parts per million?
SOLUTION Using Equation 2 with t − 1987, we estimate that the average CO2 level in
1987 was
Cs1987d − 1.78242s1987d 2 3192.90 < 348.77
This is an example of interpolation because we have estimated a value between
observed values. (In fact, the Mauna Loa Observatory reported that the average CO2
level in 1987 was 348.93 ppm, so our estimate is quite accurate.)
With t − 2025, we get
Cs2025d − 1.78242s2025d 2 3192.90 < 416.50
So we predict that the average CO2 level in the year 2025 will be 416.5 ppm. This is
an example of extrapolation because we have predicted a value outside the time
frame of observations. Consequently, we are far less certain about the accuracy of our
prediction.
Using Equation 2, we see that the CO2 level exceeds 440 ppm when
1.78242t 2 3192.90 . 440
Solving this inequality, we get
t.
3632.9
< 2038.18
1.78242
We therefore predict that the CO2 level will exceed 440 ppm by the year 2038. This
prediction is risky because it involves a time quite remote from our observations. In
fact, we see from Figure 6 that the trend has been for CO2 levels to increase rather
more rapidly in recent years, so the level might exceed 440 ppm well before 2038.
y
2
n
■ Polynomials
0
1
x
A function P is called a polynomial if
Psxd − a n x n 1 a n21 x n21 1 ∙ ∙ ∙ 1 a 2 x 2 1 a 1 x 1 a 0
(a) y=≈+x+1
where n is a nonnegative integer and the numbers a 0 , a 1, a 2 , . . . , a n are constants called
the coefficients of the polynomial. The domain of any polynomial is R − s2`, `d.
If the leading coefficient a n ± 0, then the degree of the polynomial is n. For example,
the function
y
2
Psxd − 2x 6 2 x 4 1 25 x 3 1 s2
1
x
(b) y=_2≈+3x+1
FIGURE 7
The graphs of quadratic functions
are parabolas.
is a polynomial of degree 6.
A polynomial of degree 1 is of the form Psxd − mx 1 b and so it is a linear function.
A polynomial of degree 2 is of the form Psxd − ax 2 1 bx 1 c and is called a quadratic
function. Its graph is always a parabola obtained by shifting the parabola y − ax 2, as we
will see in Section 1.3. The parabola opens upward if a . 0 and downward if a , 0.
(See Figure 7.)
A polynomial of degree 3 is of the form
Psxd − ax 3 1 bx 2 1 cx 1 d
a±0
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26
CHAPTER 1
Functions and Models
and is called a cubic function. Figure 8 shows the graph of a cubic function in part (a)
and graphs of polynomials of degrees 4 and 5 in parts (b) and (c). We will see later why
the graphs have these shapes.
y
y
1
2
0
1
20
1
x
x
(a) y=˛-x+1
FIGURE 8
y
x
1
(b) y=x$-3≈+x
(c) y=3x%-25˛+60x
Polynomials are commonly used to model various quantities that occur in the natural
and social sciences. For instance, in Section 3.7 we will explain why economists often
use a polynomial Psxd to represent the cost of producing x units of a commodity. In the
following example we use a quadratic function to model the fall of a ball.
Table 2
Time
(seconds)
Height
(meters)
0
1
2
3
4
5
6
7
8
9
450
445
431
408
375
332
279
216
143
61
EXAMPLE 4 A ball is dropped from the upper observation deck of the CN Tower,
450 m above the ground, and its height h above the ground is recorded at 1-second
intervals in Table 2. Find a model to fit the data and use the model to predict the time at
which the ball hits the ground.
SOLUTION We draw a scatter plot of the data in Figure 9 and observe that a linear
model is inappropriate. But it looks as if the data points might lie on a parabola, so we
try a quadratic model instead. Using a graphing calculator or computer algebra system
(which uses the least squares method), we obtain the following quadratic model:
h − 449.36 1 0.96t 2 4.90t 2
3
h (meters)
h
400
400
200
200
0
2
4
6
8
t
(seconds)
0
2
4
6
8
FIGURE 9
FIGURE 10
Scatter plot for a falling ball
Quadratic model for a falling ball
t
In Figure 10 we plot the graph of Equation 3 together with the data points and see
that the quadratic model gives a very good fit.
The ball hits the ground when h − 0, so we solve the quadratic equation
24.90t 2 1 0.96t 1 449.36 − 0
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.2
27
Mathematical Models: A Catalog of Essential Functions
The quadratic formula gives
t−
20.96 6 ss0.96d2 2 4s24.90ds449.36d
2s24.90d
The positive root is t < 9.67, so we predict that the ball will hit the ground after falling
about 9.7 seconds.
n
■ Power Functions
A function of the form f sxd − x a, where a is a constant, is called a power function. We
consider several cases.
( i ) a − n, where n is a positive integer
The graphs of f sxd − x n for n − 1, 2, 3, 4, and 5 are shown in Figure 11. (These are
polynomials with only one term.) We already know the shape of the graphs of y − x
(a line through the origin with slope 1) and y − x 2 [a parabola, see Example 1.1.2(b)].
y
y=x
y=≈
y
y
1
1
0
1
x
0
y=x#
y
x
0
1
x
0
y=x%
y
1
1
1
y=x$
1
1
x
0
x
1
FIGURE 11 Graphs of f sxd − x n for n − 1, 2, 3, 4, 5
The general shape of the graph of f sxd − x n depends on whether n is even or odd.
If n is even, then f sxd − x n is an even function and its graph is similar to the parabola
y − x 2. If n is odd, then f sxd − x n is an odd function and its graph is similar to that
of y − x 3. Notice from Figure 12, however, that as n increases, the graph of y − x n
becomes flatter near 0 and steeper when x > 1. (If x is small, then x 2 is smaller, x 3
is even smaller, x 4 is smaller still, and so on.)
| |
y
A family of functions is a collection
of functions whose equations are
related. Figure 12 shows two families
of power functions, one with even
powers and one with odd powers.
y=x ^
(_1, 1)
FIGURE 12
y
y=x $
y=≈
(1, 1)
0
y=x #
(1, 1)
y=x %
0
x
x
(_1, _1)
( ii ) a − 1yn, where n is a positive integer
n
The function f sxd − x 1yn − s
x is a root function. For n − 2 it is the square root
function f s xd − sx , whose domain is f0, `d and whose graph is the upper half of the
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28
CHAPTER 1
Functions and Models
n
parabola x − y 2. [See Figure 13(a).] For other even values of n, the graph of y − s
x is
3
similar to that of y − sx . For n − 3 we have the cube root function f sxd − sx whose
domain is R (recall that every real number has a cube root) and whose graph is shown
n
3
in Figure 13(b). The graph of y − s
x for n odd sn . 3d is similar to that of y − s
x.
y
y
(1, 1)
0
FIGURE 13
(1, 1)
x
0
x
(a) ƒ=œ„
Graphs of root functions
x
x
(b) ƒ=Œ„
( iii ) a 5 21
The graph of the reciprocal function f sxd − x 21 − 1yx is shown in Figure 14. Its
graph has the equation y − 1yx, or xy − 1, and is a hyperbola with the coordinate axes
as its asymptotes. This function arises in physics and chemistry in connection with
Boyle’s Law, which says that when the temperature is constant, the volume V of a gas
is inversely proportional to the pressure P:
V−
C
P
where C is a constant. Thus the graph of V as a function of P (see Figure 15) has the
same general shape as the right half of Figure 14.
y
V
y=∆
1
0
V=
1
x
0
C
P
P
FIGURE 14
FIGURE 15
The reciprocal function
Volume as a function of pressure
at constant temperature
( iv ) a 5 22
Among the remaining negative powers for the power function f sxd − x a, by far
the most important is that of a − 22. Many natural laws state that one quantity is
inversely proportional to the square of another quantity. In other words, the first
quantity is modeled by a function of the form f sxd − Cyx 2 and we refer to this as an
inverse square law. For instance, the illumination I of an object by a light source
is inversely proportional to the square of the distance x from the source:
I−
C
x2
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SECTION 1.2
29
Mathematical Models: A Catalog of Essential Functions
where C is a constant. Thus the graph of I as a function of x (see Figure 17) has the
same general shape as the right half of Figure 16.
y
I
y=
1
≈
I=
C
≈
1
0
1
0
x
x
FIGURE 16
FIGURE 17
The reciprocal of the squaring function
Illumination from a light source as a
function of distance from the source
Inverse square laws model gravitational force, loudness of sound, and electrostatic
force between two charged particles. See Exercise 37 for a geometric reason why
inverse square laws often occur in nature.
Power functions are also used to model species-area relationships (Exercises 35–36)
and the period of revolution of a planet as a function of its distance from the sun (see
Exercise 34).
■ Rational Functions
y
A rational function f is a ratio of two polynomials:
f sxd −
20
0
2
x
Psxd
Qsxd
where P and Q are polynomials. The domain consists of all values of x such that
Qsxd ± 0. A simple example of a rational function is the function f sxd − 1yx, whose
domain is hx x ± 0j; this is the reciprocal function graphed in Figure 14. The function
|
f sxd −
FIGURE 18
f sxd −
2x 4 2 x 2 1 1
x2 2 4
2x 4 2 x 2 1 1
x2 2 4
|
is a rational function with domain hx x ± 62j. Its graph is shown in Figure 18.
■ Algebraic Functions
A function f is called an algebraic function if it can be constructed using algebraic
operations (such as addition, subtraction, multiplication, division, and taking roots) starting with polynomials. Any rational function is automatically an algebraic function. Here
are two more examples:
f sxd − sx 2 1 1
tsxd −
x 4 2 16x 2
x 1 sx
3
1 sx 2 2d s
x11
In Chapter 4 we will sketch a variety of algebraic functions, and we will see that their
graphs can assume many different shapes.
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30
CHAPTER 1
Functions and Models
An example of an algebraic function occurs in the theory of relativity. The mass of a
particle with velocity v is
m − f svd −
m0
s1 2 v 2yc 2
where m 0 is the rest mass of the particle and c − 3.0 3 10 5 kmys is the speed of light in
a vacuum.
Functions that are not algebraic are called transcendental; these include the trigonometric, exponential, and logarithmic functions.
■ Trigonometric Functions
Trigonometry and the trigonometric functions are reviewed on Reference Page 2 and
also in Appendix D. In calculus the convention is that radian measure is always used
(except when otherwise indicated). For example, when we use the function f sxd − sin x,
it is understood that sin x means the sine of the angle whose radian measure is x. Thus
the graphs of the sine and cosine functions are as shown in Figure 19.
The Reference Pages are located at
the front and back of the book.
y
_
_π
π
2
y
3π
2
1
_1
0
π
2
π
_π
2π
5π
2
3π
_
x
π
2
1
π
0
_1
(a) ƒ=sin x
FIGURE 19
3π
3π
2
π
2
2π
5π
2
x
(b) ©=cos x
Notice that for both the sine and cosine functions the domain is s2`, `d and the range
is the closed interval f21, 1g. Thus, for all values of x, we have
21 < sin x < 1
21 < cos x < 1
or, in terms of absolute values,
| sin x | < 1
| cos x | < 1
An important property of the sine and cosine functions is that they are periodic functions and have period 2!. This means that, for all values of x,
sinsx 1 2!d − sin x
cossx 1 2!d − cos x
The periodic nature of these functions makes them suitable for modeling repetitive phenomena such as tides, vibrating springs, and sound waves. For instance, in Example 1.3.4
we will see that a reasonable model for the number of hours of daylight in Philadelphia
t days after January 1 is given by the function
Lstd − 12 1 2.8 sin
F
2!
st 2 80d
365
G
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SECTION 1.2
Mathematical Models: A Catalog of Essential Functions
EXAMPLE 5 Find the domain of the function f sxd −
where n is any integer (because the cosine function has period 2!). So the domain of f
is the set of all real numbers except for the ones noted above.
n
1
3π
2
1
.
1 2 2 cos x
SOLUTION This function is defined for all values of x except for those that make the
denominator 0. But
1
!
5!
1 2 2 cos x − 0 &? cos x −
&? x −
1 2n! or x −
1 2n!
2
3
3
y
_
31
0
_π _ π
2
π
2
π
3π
2
x
The tangent function is related to the sine and cosine functions by the equation
tan x −
sin x
cos x
and its graph is shown in Figure 20. It is undefined whenever cos x − 0, that is, when
x − 6!y2, 63!y2, . . . . Its range is s2`, `d. Notice that the tangent function has period !:
FIGURE 20
tansx 1 !d − tan x
y − tanxx
y=tan
for all x
The remaining three trigonometric functions (cosecant, secant, and cotangent) are
the reciprocals of the sine, cosine, and tangent functions. Their graphs are shown in
Appendix D.
y
1
0
■ Exponential Functions
y
1
0
x
1
(a) y=2®
1
x
(b) y=(0.5)®
FIGURE 21
y
■ Logarithmic Functions
The logarithmic functions f sxd − log b x, where the base b is a positive constant, are the
inverse functions of the exponential functions. They will be studied in Section 1.5. Figure 22 shows the graphs of four logarithmic functions with various bases. In each case
the domain is s0, `d, the range is s2`, `d, and the function increases slowly when x . 1.
y=log™ x
y=log£ x
1
0
1
FIGURE 22
The exponential functions are the functions of the form f sxd − b x, where the base b is
a positive constant. The graphs of y − 2 x and y − s0.5d x are shown in Figure 21. In both
cases the domain is s2`, `d and the range is s0, `d.
Exponential functions will be studied in detail in Section 1.4, and we will see that
they are useful for modeling many natural phenomena, such as when populations grow
(if b . 1) or decline (if b , 1d.
x
y=log¡¸ x
y=log∞ x
EXAMPLE 6 Classify the following functions as one of the types of functions that we
have discussed.
11x
(a) f sxd − 5 x
(b) tsxd − x 5
(c) hsxd −
(d) ustd − 1 2 t 1 5t 4
1 2 sx
SOLUTION
(a) f sxd − 5 x is an exponential function. (The variable x is the exponent.)
(b) tsxd − x 5 is a power function. (The variable x is the base.) We could also consider
it to be a polynomial of degree 5.
11x
(c) hsxd −
is an algebraic function. (It is not a rational function because the
1 2 sx
denominator is not a polynomial.)
(d) ustd − 1 2 t 1 5t 4 is a polynomial of degree 4.
n
Table 3 (on the following page) shows a summary of graphs of some families of
essential functions that will be used frequently throughout the book.
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32
CHAPTER 1
Functions and Models
Table 3 Families of Essential Functions and Their Graphs
Linear
Functions
y
y
f sxd − mx 1 b
b
b
x
0
Power
Functions
b
x
0
ƒ=b
ƒ=mx+b
y
y
y
y
f sxd − x n
x
0
x
0
ƒ=≈
Root
Functions
0
x
x
0
ƒ=˛
ƒ=x$
ƒ=x%
y
y
y
y
n
f sxd − s
x
x
0
Reciprocal
Functions
f sxd −
1
xn
0
x
x
$x
ƒ=œ„
%x
ƒ=œ„
y
y
y
y
x
0
1
x
0
0
x
1
ƒ=
≈
y
0
x
1
ƒ=
x$
y
0
1
x
1
ƒ=
˛
y
x
1
1
x
0
ƒ=b® (b>1)
Trigonometric
Functions
0
ƒ=Œ„
x
f sxd − b x
f sxd − log b x
x
ƒ= œ„
x
ƒ=
Exponential
and Logarithmic
Functions
0
0
x
ƒ=b® (b<1)
y
1
ƒ=log b x (b>1)
y
y
1
f sxd − sin x
f sxd − cos x
f sxd − tan x
0
ƒ=sin x
π
2π x
0
ƒ=cos x
π
2π
x
_
π
2
0
π
2
x
ƒ=tan x
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SECTION 1.2
33
Mathematical Models: A Catalog of Essential Functions
1.2 Exercises
1–2 Classify each function as a power function, root function,
polynomial (state its degree), rational function, algebraic function,
trigonometric function, exponential function, or logarithmic
function.
(c) r std − t s3
(d) v std − 8 t
sx
x2 1 1
(f ) tsud − log10 u
3t 2 1 2
t
(b) hsrd − 2.3 r
(c) sstd − st 1 4
(d) y − x 4 1 5
(e) tsxd − sx
1
(f ) y − 2
x
2. (a) f std −
3
3–4 Match each equation with its graph. Explain your choices.
(Don’t use a computer or graphing calculator.)
3. (a) y − x 2
(b) y − x 5
g
5. f sxd −
y
0
8. What do all members of the family of linear functions
f sxd − 1 1 msx 1 3d have in common? Sketch several
members of the family.
9. What do all members of the family of linear functions
f sxd − c 2 x have in common? Sketch several members of
the family.
11–12 Find a formula for the quadratic function whose graph is
shown.
y
18
0
4. (a) y − 3x
(b) y − 3 x
3
(d) y − sx
y
18
f
x
f
12.
y
y
(_2, 2) (_2, 2)
(0, 1) (0, 1)
f
30
(4, 2)
3
(4, 2)
x
x
g
g
0
0
x
14. Recent studies indicate that the average surface temperature of the earth has been rising steadily. Some scientists
have modeled the temperature by the linear function
T − 0.02t 1 8.50, where T is temperature in °C and t
represents years since 1900.
(a) What do the slope and T-intercept represent?
(b) Use the equation to predict the earth’s average surface
temperature in 2100.
F
g
f
x
x
(1, _2.5)(1, _2.5)
13. Find a formula for a cubic function f if f s1d − 6 and
f s21d − f s0d − f s2d − 0.
3
G
1
1 2 tan x
7. (a) Find an equation for the family of linear functions
with slope 2 and sketch several members of the
family.
(b) Find an equation for the family of linear functions
such that f s2d − 1. Sketch several members of the
family.
(c) Which function belongs to both families?
11.
y
6. tsxd −
; 10. Sketch several members of the family of polynomials
Psxd − x 3 2 cx 2. How does the graph change when c
changes?
(c) y − x 8
h
(c) y − x
cos x
1 2 sin x
(b) tstd − cos2 t 2 sin t
1. (a) f sxd − x 3 1 3x 2
(e) y −
5–6 Find the domain of the function.
15. If the recommended adult dosage for a drug is D (in mg),
then to determine the appropriate dosage c for a child of
age a, pharmacists use the equation c − 0.0417Dsa 1 1d.
Suppose the dosage for an adult is 200 mg.
(a) Find the slope of the graph of c. What does it represent?
(b) What is the dosage for a newborn?
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34
CHAPTER 1
Functions and Models
16. The manager of a weekend flea market knows from past
experience that if he charges x dollars for a rental space at
the market, then the number y of spaces that will be rented is
given by the equation y − 200 2 4x.
(a) Sketch a graph of this linear function. (Remember that
the rental charge per space and the number of spaces
rented can’t be negative quantities.)
(b) What do the slope, the y-intercept, and the x-intercept of
the graph represent?
17. The relationship between the Fahrenheit sFd and Celsius sCd
temperature scales is given by the linear function F − 95 C 1 32.
(a) Sketch a graph of this function.
(b) What is the slope of the graph and what does it represent?
What is the F-intercept and what does it represent?
18. Jade and her roommate Jari commute to work each morning,
traveling west on I-10. One morning Jade left for work at
6:50 am, but Jari left 10 minutes later. Both drove at a constant speed. The graphs show the distance (in miles) each of
them has traveled on I-10, t minutes after 7:00 am.
(a) Use the graph to decide which driver is traveling faster.
(b) Find the speed (in miyh) at which each of them is driving.
(c) Find linear functions f and t that model the distances
traveled by Jade and Jari as functions of t (in minutes).
Distance traveled
(mi)
y
30
20
(6, 16)
10
(6, 7)
0
3
6
Jade
Jari
9
12
t
Time since 7:00 AM (min)
19. The manager of a furniture factory finds that it costs $2200 to
manufacture 100 chairs in one day and $4800 to produce
300 chairs in one day.
(a) Express the cost as a function of the number of chairs
produced, assuming that it is linear. Then sketch the graph.
(b) What is the slope of the graph and what does it represent?
(c) What is the y-intercept of the graph and what does it
represent?
20. The monthly cost of driving a car depends on the number of
miles driven. Lynn found that in May it cost her $380 to drive
480 mi and in June it cost her $460 to drive 800 mi.
(a) Express the monthly cost C as a function of the distance
driven d, assuming that a linear relationship gives a
suitable model.
(b) Use part (a) to predict the cost of driving 1500 miles per
month.
(c) Draw the graph of the linear function. What does the
slope represent?
(d) What does the C-intercept represent?
(e) Why does a linear function give a suitable model in this
situation?
21. At the surface of the ocean, the water pressure is the same
as the air pressure above the water, 15 lbyin2. Below the surface, the water pressure increases by 4.34 lbyin2 for every
10 ft of descent.
(a) Express the water pressure as a function of the depth
below the ocean surface.
(b) At what depth is the pressure 100 lbyin2 ?
22. The resistance R of a wire of fixed length is related to its
diameter x by an inverse square law, that is, by a function of
the form Rsxd − kx 22.
(a) A wire of fixed length and 0.005 meters in diameter has a
resistance of 140 ohms. Find the value of k.
(b) Find the resistance of a wire made of the same material
and of the same length as the wire in part (a) but with a
diameter of 0.008 meters.
23. The illumination of an object by a light source is related to
the distance from the source by an inverse square law. Suppose that after dark you are sitting in a room with just one
lamp, trying to read a book. The light is too dim, so you move
your chair halfway to the lamp. How much brighter is the
light?
24. The pressure P of a sample of oxygen gas that is compressed
at a constant temperature is related to the volume V of gas by
a reciprocal function of the form P − kyV.
(a) A sample of oxygen gas that occupies 0.671 m3 exerts a
pressure of 39 kPa at a temperature of 293 K (absolute
temperature measured on the Kelvin scale). Find the
value of k in the given model.
(b) If the sample expands to a volume of 0.916 m3, find the
new pressure.
25. The power output of a wind turbine depends on many factors.
It can be shown using physical principles that the power P
generated by a wind turbine is modeled by
P − kAv 3
where v is the wind speed, A is the area swept out by the
blades, and k is a constant that depends on air density,
efficiency of the turbine, and the design of the wind turbine
blades.
(a) If only wind speed is doubled, by what factor is the
power output increased?
(b) If only the length of the blades is doubled, by what factor
is the power output increased?
(c) For a particular wind turbine, the length of the blades is
30 m and k − 0.214 kgym3. Find the power output (in
watts, W − m2 ? kgys3 ) when the wind speed is 10 mys,
15 mys, and 25 mys.
26. Astronomers infer the radiant exitance (radiant flux
emitted per unit area) of stars using the Stefan Boltzmann
Law:
EsT d − s5.67 3 1028 dT 4
where E is the energy radiated per unit of surface area
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SECTION 1.2
measured in watts (W) and T is the absolute temperature
measured in kelvins (K).
(a) Graph the function E for temperatures T between
100 K and 300 K.
(b) Use the graph to describe the change in energy E as
the temperature T increases.
30. When laboratory rats are exposed to asbestos fibers, some of
them develop lung tumors. The table lists the results of several experiments by different scientists.
(a) Find the regression line for the data.
(b) Make a scatter plot and graph the regression line.
Does the regression line appear to be a suitable model
for the data?
(c) What does the y-intercept of the regression line represent?
27–28 For each scatter plot, decide what type of function you
might choose as a model for the data. Explain your choices.
27. (a)
y
(b) y
(b)
0
x
Asbestos Percent of mice
exposure
that develop
(fibersymL)
lung tumors
0
50
400
500
900
1100
x
(b)
(b) y
28. (a)
(a) y
0
x
0
x
29. The table shows (lifetime) peptic ulcer rates (per 100 population) for various family incomes as reported by the National
Health Interview Survey.
(a) Make a scatter plot of these data and decide whether a
linear model is appropriate.
(b) Find and graph a linear model using the first and last
data points.
(c) Find and graph the regression line.
(d) Use the linear model in part (c) to estimate the ulcer rate
for people with an income of $25,000.
(e) According to the model, how likely is someone with
an income of $80,000 to suffer from peptic ulcers?
(f ) Do you think it would be reasonable to apply the
model to someone with an income of $200,000?
Income
Ulcer rate
(per 100 population)
$4,000
$6,000
$8,000
$12,000
$16,000
$20,000
$30,000
$45,000
$60,000
14.1
13.0
13.4
12.5
12.0
12.4
10.5
9.4
8.2
35
Mathematical Models: A Catalog of Essential Functions
2
6
5
10
26
Asbestos
exposure
(fibersymL)
Percent of mice
that develop
lung tumors
1600
1800
2000
3000
42
37
38
50
31. Anthropologists use a linear model that relates human femur
(thighbone) length to height. The model allows an anthropologist to determine the height of an individual when only a
partial skeleton (including the femur) is found. Here we find
the model by analyzing the data on femur length and height
for the eight males given in the table.
(a) Make a scatter plot of the data.
(b) Find and graph the regression line that models the data.
(c) An anthropologist finds a human femur of length
53 cm. How tall was the person?
Femur length
(cm)
Height
(cm)
Femur length
(cm)
Height
(cm)
50.1
48.3
45.2
44.7
178.5
173.6
164.8
163.7
44.5
42.7
39.5
38.0
168.3
165.0
155.4
155.8
32. The table shows average US retail residential prices of
electricity from 2000 to 2016, measured in cents per kilowatt hour.
(a) Make a scatter plot. Is a linear model appropriate?
(b) Find and graph the regression line.
(c) Use your linear model from part (b) to estimate the
average retail price of electricity in 2005 and 2017.
Years since 2000 CentsykWh Years since 2000 CentsykWh
0
2
4
6
8
8.24
8.44
8.95
10.40
11.26
10
12
14
16
11.54
11.88
12.52
12.90
Source: US Energy Information Administration
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36
CHAPTER 1
Functions and Models
33. The table shows world average daily oil consumption from
1985 to 2015, measured in thousands of barrels per day.
(a) Make a scatter plot and decide whether a linear model is
appropriate.
(b) Find and graph the regression line.
(c) Use the linear model to estimate the oil consumption in
2002 and 2017.
Years
since 1985
Thousands of barrels
of oil per day
0
5
10
15
20
25
30
60,083
66,533
70,099
76,784
84,077
87,302
94,071
Source: US Energy Information Administration
34. The table shows the mean (average) distances d of the planets from the sun (taking the unit of measurement to be the
distance from the earth to the sun) and their periods T (time
of revolution in years).
(a) Fit a power model to the data.
(b) Kepler’s Third Law of Planetary Motion states that
“The square of the period of revolution of a planet is
proportional to the cube of its mean distance from the sun.”
Does your model corroborate Kepler’s Third Law?
Planet
d
T
Mercury
Venus
Earth
Mars
Jupiter
Saturn
Uranus
Neptune
0.387
0.723
1.000
1.523
5.203
9.541
19.190
30.086
0.241
0.615
1.000
1.881
11.861
29.457
84.008
164.784
35. It makes sense that the larger the area of a region, the
larger the number of species that inhabit the region.
Many ecologists have modeled the species-area relation
with a power function. In particular, the number of
species S of bats living in caves in central Mexico has
been related to the surface area A of the caves by the
equation S − 0.7A0.3.
(a) The cave called Misión Imposible near Puebla,
Mexico, has a surface area of A − 60 m2. How
many species of bats would you expect to find in
that cave?
(b) If you discover that four species of bats live in a cave,
estimate the area of the cave.
36. The table shows the number N of species of reptiles and
amphibians inhabiting Caribbean islands and the area A of
the island in square miles.
(a) Use a power function to model N as a function
of A.
(b) The Caribbean island of Dominica has area 291 mi 2.
How many species of reptiles and amphibians would
you expect to find on Dominica?
Island
A
N
Saba
4
5
Monserrat
40
9
Puerto Rico
3,459
40
Jamaica
4,411
39
Hispaniola
29,418
84
Cuba
44,218
76
37. Suppose that a force or energy originates from a point
source and spreads its influence equally in all directions,
such as the light from a lightbulb or the gravitational force
of a planet. So at a distance r from the source, the intensity
I of the force or energy is equal to the source strength S
divided by the surface area of a sphere of radius r. Show
that I satisfies the inverse square law I − kyr 2, where k is
a positive constant.
1.3 New Functions from Old Functions
In this section we start with the basic functions we discussed in Section 1.2 and obtain
new functions by shifting, stretching, and reflecting their graphs. We also show how to
combine pairs of functions by the standard arithmetic operations and by composition.
■ Transformations of Functions
By applying certain transformations to the graph of a given function we can obtain
the graphs of related functions. This will give us the ability to sketch the graphs of
many functions quickly by hand. It will also enable us to write equations for given graphs.
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SECTION 1.3
37
New Functions from Old Functions
Let’s first consider translations of graphs. If c is a positive number, then the graph of
y − f sxd 1 c is just the graph of y − f sxd shifted upward a distance of c units (because
each y-coordinate is increased by the same number c). Likewise, if tsxd − f sx 2 cd,
where c . 0, then the value of t at x is the same as the value of f at x 2 c (c units to the
left of x). Therefore the graph of y − f sx 2 cd is just the graph of y − f sxd shifted c units
to the right (see Figure 1).
Vertical and Horizontal Shifts Suppose c . 0. To obtain the graph of
y − f sxd 1 c, shift the graph of y − f sxd a distance c units upward
y − f sxd 2 c, shift the graph of y − f sxd a distance c units downward
y − f sx 2 cd, shift the graph of y − f sxd a distance c units to the right
y − f sx 1 cd, shift the graph of y − f sxd a distance c units to the left
y
y
y=ƒ+c
y=f(x+c)
c
y =ƒ
c
0
y=cƒ
(c>1)
y=f(_x)
y=f(x-c)
y=ƒ
y= 1c ƒ
c
x
c
x
0
y=ƒ-c
y=_ƒ
FIGURE 1 Translating the graph of f
FIGURE 2 Stretching and reflecting the graph of f
Now let’s consider the stretching and reflecting transformations. If c . 1, then the
graph of y − cf sxd is the graph of y − f sxd stretched by a factor of c in the vertical
direction (because each y-coordinate is multiplied by the same number c). The graph of
y − 2f sxd is the graph of y − f sxd reflected about the x-axis because the point sx, yd is
replaced by the point sx, 2yd. (See Figure 2 and the following chart, where the results of
other stretching, shrinking, and reflecting transformations are also given.)
Vertical and Horizontal Stretching and Reflecting Suppose c . 1. To obtain the
graph of
y − cf sxd, stretch the graph of y − f sxd vertically by a factor of c
y − s1ycdf sxd, shrink the graph of y − f sxd vertically by a factor of c
y − f scxd, shrink the graph of y − f sxd horizontally by a factor of c
y − f sxycd, stretch the graph of y − f sxd horizontally by a factor of c
y − 2f sxd, reflect the graph of y − f sxd about the x-axis
y − f s2xd, reflect the graph of y − f sxd about the y-axis
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38
CHAPTER 1
Functions and Models
Figure 3 illustrates these stretching transformations when applied to the cosine function with c − 2. For instance, in order to get the graph of y − 2 cos x we multiply the
y-coordinate of each point on the graph of y − cos x by 2. This means that the graph of
y − cos x gets stretched vertically by a factor of 2.
y
y=2 cos x
y
2
y=cos x
2
1
0
y=cos 1 x
y=cos 2x
2
1
1
y= cos x
2
x
1
0
x
y=cos x
FIGURE 3
EXAMPLE 1 Given the graph of y − sx , use transformations to graph y − sx 2 2,
y − sx 2 2 , y − 2sx , y − 2sx , and y − s2x .
SOLUTION The graph of the square root function y − sx , obtained from Figure 1.2.13(a), is shown in Figure 4(a). In the other parts of the figure we sketch
y − sx 2 2 by shifting 2 units downward, y − sx 2 2 by shifting 2 units to the
right, y − 2sx by reflecting about the x-axis, y − 2sx by stretching vertically by a
factor of 2, and y − s2x by reflecting about the y-axis.
y
y
y
y
y
y
1
0
x
1
x
0
0
x
2
x
0
x
0
0
x
_2
(a) y=œ„x
(b) y=œ„-2
x
(d) y=_ œ„x
(c) y=œ„„„„
x-2
(f) y=œ„„
_x
(e) y=2 œ„x
FIGURE 4
n
EXAMPLE 2 Sketch the graph of the function f sxd − x 2 1 6x 1 10.
SOLUTION Completing the square, we write the equation of the graph as
y − x 2 1 6x 1 10 − sx 1 3d2 1 1
This means we obtain the desired graph by starting with the parabola y − x 2 and
shifting 3 units to the left and then 1 unit upward (see Figure 5).
y
y
1
(_3, 1)
0
FIGURE 5
(a) y=≈
x
_3
_1
0
(b) y=(x+3)@+1
x
n
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SECTION 1.3
39
New Functions from Old Functions
EXAMPLE 3 Sketch the graph of each function.
(a) y − sin 2x
(b) y − 1 2 sin x
SOLUTION
(a) We obtain the graph of y − sin 2x from that of y − sin x by compressing horizontally by a factor of 2. (See Figures 6 and 7.) Because the period of y − sin x is 2!,
the period of y − sin 2x is 2!y2 − !.
y
y
y=sin x
1
0
π
2
π
y=sin 2x
1
2π
x
0 π π
4
FIGURE 6
x
π
2
FIGURE 7
(b) To obtain the graph of y − 1 2 sin x, we again start with y − sin x. We reflect
about the x-axis to get the graph of y − 2sin x and then we shift 1 unit upward to get
y − 1 2 sin x. (See Figure 8.)
y
y=1-sin x
2
1
0
FIGURE 8
π
2
π
3π
2
x
2π
n
EXAMPLE 4 Figure 9 shows graphs of the number of hours of daylight as functions of
the time of the year at several latitudes. Given that Philadelphia is located at approximately 408N latitude, find a function that models the length of daylight at Philadelphia.
20
18
16
14
12
20° N
30° N
40° N
50° N
Hours 10
8
FIGURE 9
Graph of the length of daylight from
March 21 through December 21
at various latitudes
Source: Adapted from L. Harrison,
Daylight, Twilight, Darkness and Time
(New York: Silver, Burdett, 1935), 40.
6
60° N
4
2
0
Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.
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40
CHAPTER 1
Functions and Models
SOLUTION Notice that each curve resembles a shifted and stretched sine function.
By looking at the blue curve we see that, at the latitude of Philadelphia, daylight
lasts about 14.8 hours on June 21 and 9.2 hours on December 21, so the amplitude
of the curve (the factor by which we have to stretch the sine curve vertically) is
1
2 s14.8 2 9.2d − 2.8.
By what factor do we need to stretch the sine curve horizontally if we measure the
time t in days? Because there are about 365 days in a year, the period of our model
should be 365. But the period of y − sin t is 2!, so the horizontal stretching factor
is 2!y365.
We also notice that the curve begins its cycle on March 21, the 80th day of the year,
so we have to shift the curve 80 units to the right. In addition, we shift it 12 units
upward. Therefore we model the length of daylight in Philadelphia on the t th day of the
year by the function
2!
Lstd − 12 1 2.8 sin
st 2 80d
365
n
F
y
_1
0
1
x
(a) y=≈-1
_1
Another transformation of some interest is taking the absolute value of a function. If
y − f sxd , then according to the definition of absolute value, y − f sxd when f sxd > 0
and y − 2f sxd when f sxd , 0. This tells us how to get the graph of y − f sxd from the
graph of y − f sxd: the part of the graph that lies above the x-axis remains the same, and
the part that lies below the x-axis is reflected about the x-axis.
|
|
|
|
y
EXAMPLE 5 Sketch the graph of the function y − | x 2 2 1 |.
0
SOLUTION We first graph the parabola y − x 2 2 1 in Figure 10(a) by shifting the
parabola y − x 2 downward 1 unit. We see that the graph lies below the x-axis when
21 , x , 1, so we reflect that part of the graph about the x-axis to obtain the graph of
y − x 2 2 1 in Figure 10(b).
n
1
(b) y=| ≈-1 |
FIGURE 10
G
x
|
|
■ Combinations of Functions
Two functions f and t can be combined to form new functions f 1 t, f 2 t, ft, and fyt
in a manner similar to the way we add, subtract, multiply, and divide real numbers.
Definition Given two functions f and t, the sum, difference, product, and
quotient functions are defined by
s f 1 tdsxd − f sxd 1 tsxd
s f 2 tdsxd − f sxd 2 tsxd
s ftdsxd − f sxd tsxd
f
f sxd
sxd −
t
tsxd
SD
If the domain of f is A and the domain of t is B, then the domain of f 1 t (and the
domain of f 2 t) is the intersection A > B because both f sxd and tsxd have to be defined.
For example, the domain of f sxd − sx is A − f0, `d and the domain of tsxd − s2 2 x
is B − s2`, 2g, so the domain of s f 1 tdsxd − sx 1 s2 2 x is A > B − f0, 2g.
The domain of ft is also A > B. Because we can’t divide by 0, the domain of fyt is
hx [ A > B tsxd ± 0j. For instance, if f sxd − x 2 and tsxd − x 2 1, then the domain
of the rational function s fytdsxd − x 2ysx 2 1d is hx x ± 1j, or s2`, 1d ø s1, `d.
There is another way of combining two functions to obtain a new function. For
example, suppose that y − f sud − su and u − tsxd − x 2 1 1. Since y is a function
|
|
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SECTION 1.3
New Functions from Old Functions
41
of u and u is, in turn, a function of x, it follows that y is ultimately a function of x.
We compute this by substitution:
y − f sud − f stsxdd − f sx 2 1 1d − sx 2 1 1
x (input)
g
©
f•g
The procedure is called composition because the new function is composed of the two
given functions f and t.
In general, given any two functions f and t, we start with a number x in the domain
of t and calculate tsxd. If this number tsxd is in the domain of f, then we can calculate
the value of f stsxdd. Notice that the output of one function is used as the input to the next
function. The result is a new function hsxd − f s tsxdd obtained by substituting t into f. It
is called the composition (or composite) of f and t and is denoted by f 8 t (“ f circle t”).
Definition Given two functions f and t, the composite function f 8 t (also
called the composition of f and t) is defined by
f
s f 8 tdsxd − f s tsxdd
f { ©} (output)
FIGURE 11
The f 8 t machine is composed of
the t machine (first) and then the
f machine.
The domain of f 8 t is the set of all x in the domain of t such that tsxd is in the domain
of f. In other words, s f 8 tdsxd is defined whenever both tsxd and f s tsxdd are defined.
Figure 11 shows how to picture f 8 t in terms of machines.
EXAMPLE 6 If f sxd − x 2 and tsxd − x 2 3, find the composite functions f 8 t and t 8 f.
SOLUTION We have
s f 8 tdsxd − f s tsxdd − f sx 2 3d − sx 2 3d2
s t 8 f dsxd − ts f sxdd − tsx 2 d − x 2 2 3
n
NOTE You can see from Example 6 that, in general, f 8 t ± t 8 f. Remember, the
notation f 8 t means that the function t is applied first and then f is applied second. In
Example 6, f 8 t is the function that first subtracts 3 and then squares; t 8 f is the function
that first squares and then subtracts 3.
EXAMPLE 7 If f sxd − sx and tsxd − s2 2 x , find each function and its domain.
(a) f 8 t
SOLUTION
(a)
(b) t 8 f
(d) t 8 t
(c) f 8 f
4
s f 8 tdsxd − f stsxdd − f (s2 2 x ) − ss2 2 x − s
22x
|
|
The domain of f 8 t is hx 2 2 x > 0j − hx x < 2j − s2`, 2g.
(b)
If 0 < a < b, then a 2 < b 2.
s t 8 f dsxd − ts f sxdd − t (sx ) − s2 2 sx
For sx to be defined we must have x > 0. For s2 2 sx to be defined we must have
2 2 sx > 0, that is, sx < 2, or x < 4. Thus we have 0 < x < 4, so the domain of
t 8 f is the closed interval f0, 4g.
(c)
4
s f 8 f dsxd − f s f sxdd − f (sx ) − ssx − s
x
The domain of f 8 f is f0, `d.
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42
CHAPTER 1
Functions and Models
st 8 tdsxd − ts tsxdd − t (s2 2 x ) − s2 2 s2 2 x
(d)
This expression is defined when both 2 2 x > 0 and 2 2 s2 2 x > 0. The first
inequality means x < 2, and the second is equivalent to s2 2 x < 2, or 2 2 x < 4, or
x > 22. Thus 22 < x < 2, so the domain of t 8 t is the closed interval f22, 2g.
n
It is possible to take the composition of three or more functions. For instance, the
composite function f 8 t 8 h is found by first applying h, then t, and then f as follows:
s f 8 t 8 hdsxd − f stshsxddd
EXAMPLE 8 Find f 8 t 8 h if f sxd − xysx 1 1d, tsxd − x 10, and hsxd − x 1 3.
SOLUTION
s f 8 t 8 hdsxd − f stshsxddd − f stsx 1 3dd
sx 1 3d10
− f ssx 1 3d10 d −
sx 1 3d10 1 1
n
So far we have used composition to build complicated functions from simpler ones.
But in calculus it is often useful to be able to decompose a complicated function into
simpler ones, as in the following example.
EXAMPLE 9 Given Fsxd − cos2sx 1 9d, find functions f , t, and h such that F − f 8 t 8 h.
SOLUTION Since Fsxd − fcossx 1 9dg 2, the formula for F says: first add 9, then take
the cosine of the result, and finally square. So we let
tsxd − cos x
hsxd − x 1 9
Then
1.3
f sxd − x 2
s f 8 t 8 hdsxd − f stshsxddd − f stsx 1 9dd − f scossx 1 9dd
− fcossx 1 9dg 2 − Fsxd
n
Exercises
1. Suppose the graph of f is given. Write equations for the
graphs that are obtained from the graph of f as follows.
(a) Shift 3 units upward.
3. The graph of y − f sxd is given. Match each equation with its
graph and give reasons for your choices.
(a) y − f sx 2 4d
(b) y − f sxd 1 3
(b) Shift 3 units downward.
(c) y − 13 f sxd
(c) Shift 3 units to the right.
(e) y − 2 f sx 1 6d
(d) Shift 3 units to the left.
(d) y − 2f sx 1 4d
y
@
(e) Reflect about the x-axis.
6
!
(f ) Reflect about the y-axis.
(g) Stretch vertically by a factor of 3.
3
(h) Shrink vertically by a factor of 3.
2. Explain how each graph is obtained from the graph
of y − f sxd.
(a) y − f sxd 1 8
(b) y − f sx 1 8d
(c) y − 8 f sxd
(d) y − f s8xd
(e) y − 2f sxd 2 1
(f) y − 8 f ( 18 x)
f
#
$
_6
_3
%
0
3
6
x
_3
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SECTION 1.3
4. The graph of f is given. Draw the graphs of the following
functions.
(a) y − f sxd 2 3
(b) y − f sx 1 1d
(c)
y − 12 f sxd
(d) y − 2f sxd
y
1
12
x
1
x
16. y − 1 1
17. y − 2 1 sx 1 1
18. y − 2sx 2 1d2 1 3
19. y − x 2 2 2x 1 5
20. y − sx 1 1d3 1 2
21. y − 2 2 x
22. y − 2 2 2 cos x
23. y − 3 sin 12 x 1 1
24. y −
|
5. The graph of f is given. Use it to graph the following
functions.
(a) y − f s2xd
(b) y − f ( 12 x)
(c) y − f s2xd
y
1
x
1
6–7 The graph of y − s3x 2 x 2 is given. Use transformations
to create a function whose graph is as shown.
y
y=œ„„„„„„
3x-≈
1.5
0
6.
x
3
7.
y
3
y
_4
0
5
2
_1 0
x
_1
_2.5
x
8. (a) How is the graph of y − 1 1 sx related to the graph of
y − sx ? Use your answer and Figure 4(a) to sketch the
graph of y − 1 1 sx .
(b) How is the graph of y − 5 sin !x related to the graph of
y − sin x ? Use your answer and Figure 6 to sketch the
graph of y − 5 sin !x .
9–26 Graph the function by hand, not by plotting points, but by
starting with the graph of one of the standard functions given in
Table 1.2.3, and then applying the appropriate transformations.
10. y − sx 1 1d2
9. y − 1 1 x 2
|
11. y − x 1 2
|
|
S D
1
!
tan x 2
4
4
|
26. y − sx 2 1
|
27. The city of New Orleans is located at latitude 30°N. Use Figure 9 to find a function that models the number of hours of daylight at New Orleans as a function of the time of year. To check
the accuracy of your model, use the fact that on March 31 the
sun rises at 5:51 am and sets at 6:18 pm in New Orleans.
(d) y − 2f s2xd
0
1
x2
15. y − sin 4x
25. y − cos !x
43
14. y − 2sx 2 1
| |
2
0
13. y −
New Functions from Old Functions
28. A variable star is one whose brightness alternately increases
and decreases. For the most visible variable star, Delta Cephei,
the time between periods of maximum brightness is 5.4 days,
the average brightness (or magnitude) of the star is 4.0, and its
brightness varies by 60.35 magnitude. Find a function that
models the brightness of Delta Cephei as a function of time.
29. Some of the highest tides in the world occur in the Bay of
Fundy on the Atlantic Coast of Canada. At Hopewell Cape
the water depth at low tide is about 2.0 m and at high tide
it is about 12.0 m. The natural period of oscillation is
about 12 hours and on a particular day, high tide occurred
at 6:45 am. Find a function involving the cosine function
that models the water depth Dstd (in meters) as a function
of time t (in hours after midnight) on that day.
30. In a normal respiratory cycle the volume of air that moves
into and out of the lungs is about 500 mL. The reserve and
residue volumes of air that remain in the lungs occupy about
2000 mL and a single respiratory cycle for an average human
takes about 4 seconds. Find a model for the total volume of
air Vstd in the lungs as a function of time.
| |
| |
| |
31. (a) How is the graph of y − f ( x ) related to the graph of f ?
(b) Sketch the graph of y − sin x .
(c) Sketch the graph of y − s x .
32. Use the given graph of f to sketch the graph of y − 1yf sxd.
Which features of f are the most important in sketching
y − 1yf sxd? Explain how they are used.
y
1
0
1
x
12. y − 1 2 x 3
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
44
CHAPTER 1
Functions and Models
33–34 Find (a) f 1 t, (b) f 2 t, (c) f t, and (d) fyt and state their
domains.
33. f sxd − s25 2 x 2,
1
,
x21
34. f sxd −
tsxd − sx 1 1
tsxd −
1
22
x
35– 40 Find the functions (a) f 8 t, (b) t 8 f , (c) f 8 f , and (d) t 8 t
and their domains.
1
,
x
sx
2
,
x
y
3
g
0
58. Use the given graphs of f and t to estimate the value of
f s tsxdd for x − 25, 24, 23, . . . , 5. Use these estimates to
sketch a rough graph of f 8 t.
tsxd − sx 2 1
40. f sxd − s5 2 x ,
y
41– 44 Find f 8 t 8 h.
g
tsxd − sin x,
hsxd − x 2
42. f sxd − x 2 4 ,
tsxd − 2 x,
hsxd − sx
43. f sxd − sx 2 3 ,
tsxd − x 2,
hsxd − x 3 1 2
41. f sxd − 3x 2 2,
|
tsxd −
44. f sxd − tan x,
1
0
x
3
, hsxd − s
x
x21
45. Fsxd − s2 x 1 x 2 d 4
46. Fsxd − cos2 x
3
x
s
48. Gsxd −
1 1 sx
3
49. v std − secst 2 d tanst 2 d
Î
3
51. Rsxd − ssx 2 1
x
11x
50. Hsxd − s1 1 sx
51–54 Express the function in the form f 8 t 8 h.
| |
8
52. Hsxd − s
21 x
54. Hstd − cos (s tan t 1 1)
53. Sstd − sin2scos td
55–56 Use the table to evaluate each expression.
x
1
2
3
4
5
6
f sxd
3
1
5
6
2
4
tsxd
5
3
4
1
3
2
55. (a) f s ts3dd
(c) s f 8 tds5d
(b) ts f s2dd
(d) s t 8 f ds5d
1
x
f
45–50 Express the function in the form f 8 t.
47. Fsxd −
x
2
tsxd − 2x 2 1
tsxd − sin x
|
f
2
tsxd − x 1 1
,
x
38. f sxd −
,
x11
39. f sxd −
57. Use the given graphs of f and t to evaluate each expression,
or explain why it is undefined.
(a) f s ts2dd
(b) ts f s0dd
(c) s f 8 tds0d
(d) s t 8 f ds6d
(e) s t 8 tds22d
(f) s f 8 f ds4d
tsxd − 2x 1 1
1
37. f sxd −
(b) s f + f + f ds1d
(d) s t + f + tds3d
tsxd − sx
35. f sxd − x 1 5,
3
36. f sxd −
56. (a) ts ts ts2ddd
(c) s f + f + tds1d
59. A stone is dropped into a lake, creating a circular ripple that
travels outward at a speed of 60 cmys.
(a) Express the radius r of this circle as a function of the
time t (in seconds).
(b) If A is the area of this circle as a function of the radius,
find A 8 r and interpret it.
60. A spherical balloon is being inflated and the radius of the
balloon is increasing at a rate of 2 cmys.
(a) Express the radius r of the balloon as a function of the
time t (in seconds).
(b) If V is the volume of the balloon as a function of the
radius, find V 8 r and interpret it.
61. A ship is moving at a speed of 30 kmyh parallel to a straight
shoreline. The ship is 6 km from shore and it passes a lighthouse at noon.
(a) Express the distance s between the lighthouse and the
ship as a function of d, the distance the ship has traveled
since noon; that is, find f so that s − f sd d.
(b) Express d as a function of t, the time elapsed since noon;
that is, find t so that d − tstd.
(c) Find f 8 t. What does this function represent?
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SECTION 1.4
62. An airplane is flying at a speed of 350 miyh at an altitude
of one mile and passes directly over a radar station at
time t − 0.
(a) Express the horizontal distance d (in miles) that the plane
has flown as a function of t.
(b) Express the distance s between the plane and the radar
station as a function of d.
(c) Use composition to express s as a function of t.
63. The Heaviside Function The Heaviside function H is defined by
H
0 if t , 0
Hstd −
1 if t > 0
It is used in the study of electric circuits to represent the sudden surge of electric current, or voltage, when a switch is
instantaneously turned on.
(a) Sketch the graph of the Heaviside function.
(b) Sketch the graph of the voltage Vstd in a circuit if the
switch is turned on at time t − 0 and 120 volts are
applied instantaneously to the circuit. Write a formula
for Vstd in terms of Hstd.
(c) Sketch the graph of the voltage Vstd in a circuit if the
switch is turned on at time t − 5 seconds and 240 volts
are applied instantaneously to the circuit. Write a formula
for Vstd in terms of Hstd. (Note that starting at t − 5
corresponds to a translation.)
64. The Ramp Function The Heaviside function defined in
Exercise 63 can also be used to define the ramp function
y − ctHstd, which represents a gradual increase in voltage or
current in a circuit.
(a) Sketch the graph of the ramp function y − tHstd.
(b) Sketch the graph of the voltage Vstd in a circuit if the
switch is turned on at time t − 0 and the voltage is gradually increased to 120 volts over a 60-second time interval.
Write a formula for Vstd in terms of Hstd for t < 60.
Exponential Functions
45
(c) Sketch the graph of the voltage Vstd in a circuit if the
switch is turned on at time t − 7 seconds and the
voltage is gradually increased to 100 volts over a period
of 25 seconds. Write a formula for Vstd in terms of Hstd
for t < 32.
65. Let f and t be linear functions with equations
f sxd − m1 x 1 b1 and tsxd − m 2 x 1 b 2. Is f 8 t also a
linear function? If so, what is the slope of its graph?
66. If you invest x dollars at 4% interest compounded annually,
then the amount Asxd of the investment after one year is
Asxd − 1.04x. Find A 8 A, A 8 A 8 A, and A 8 A 8 A 8 A. What
do these compositions represent? Find a formula for the composition of n copies of A.
67. (a) If tsxd − 2x 1 1 and hsxd − 4x 2 1 4x 1 7, find a function f such that f 8 t − h. (Think about what operations
you would have to perform on the formula for t to end up
with the formula for h.)
(b) If f sxd − 3x 1 5 and hsxd − 3x 2 1 3x 1 2, find a
function t such that f 8 t − h.
68. If f sxd − x 1 4 and hsxd − 4x 2 1, find a function t such
that t 8 f − h.
69. Suppose t is an even function and let h − f 8 t. Is h always an
even function?
70. Suppose t is an odd function and let h − f 8 t. Is h always an
odd function? What if f is odd? What if f is even?
71. Let f sxd be a function with domain R .
(a) Show that Esxd − f sxd 1 f s2xd is an even function.
(b) Show that Osxd − f sxd 2 f s2xd is an odd function.
(c) Prove that every function f sxd can be written as a sum of
an even function and an odd function.
(d) Express the function f sxd − 2 x 1 sx 2 3d2 as a sum of
an even function and an odd function.
1.4 Exponential Functions
The function f sxd − 2 x is called an exponential function because the variable, x, is the
exponent. It should not be confused with the power function tsxd − x 2, in which the variable is the base.
■ Exponential Functions and Their Graphs
In general, an exponential function is a function of the form
f sxd − b x
In Appendix G we present an alternative approach to the exponential
and logarithmic functions using
integral calculus.
where b is a positive constant. Let’s recall what this means.
If x − n, a positive integer, then
bn − b ? b ? ∙ ∙ ∙ ? b
n factors
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46
CHAPTER 1
Functions and Models
If x − 0, then b 0 − 1, and if x − 2n, where n is a positive integer, then
b 2n −
y
1
bn
If x is a rational number, x − pyq, where p and q are integers and q . 0, then
q
q
b x − b pyq − s
b − (s
b)
p
1
0
1
x
FIGURE 1
Representation of y − 2 x, x rational
p
But what is the meaning of b x if x is an irrational number? For instance, what is meant
by 2 s3 or 5! ?
To help us answer this question we first look at the graph of the function y − 2 x,
where x is rational. A representation of this graph is shown in Figure 1. We want to
enlarge the domain of y − 2 x to include both rational and irrational numbers.
There are holes in the graph in Figure 1 corresponding to irrational values of x. We
want to fill in the holes by defining f sxd − 2 x, where x [ R, so that f is an increasing
function. In particular, since the irrational number s3 satisfies
1.7 , s3 , 1.8
2 1.7 , 2 s3 , 2 1.8
we must have
and we know what 21.7 and 21.8 mean because 1.7 and 1.8 are rational numbers. Similarly,
if we use better approximations for s3 , we obtain better approximations for 2 s3:
1.73 , s3 , 1.74
?
2 1.73 , 2 s3 , 2 1.74
1.732 , s3 , 1.733
?
2 1.732 , 2 s3 , 2 1.733
1.7320 , s3 , 1.7321
?
2 1.7320 , 2 s3 , 2 1.7321
1.73205 , s3 , 1.73206 ? 2 1.73205 , 2 s3 , 2 1.73206
.
.
.
.
.
.
.
.
.
.
.
.
A proof of this fact is given in
J. Marsden and A. Weinstein, Calculus
Unlimited (Menlo Park, CA: Benjamin/
Cummings, 1981).
It can be shown that there is exactly one number that is greater than all of the numbers
2 1.7,
2 1.73,
2 1.732,
2 1.7320,
2 1.73205,
...
2 1.733,
2 1.7321,
2 1.73206,
...
and less than all of the numbers
2 1.8,
2 1.74,
s3
We define 2 to be this number. Using the preceding approximation process we can
compute it correct to six decimal places:
2 s3 < 3.321997
Similarly, we can define 2 x (or b x, if b . 0) where x is any irrational number. Figure 2 shows how all the holes in Figure 1 have been filled to complete the graph of the
function f sxd − 2 x, x [ R.
y
1
FIGURE 2
y − 2 x, x real
0
1
x
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SECTION 1.4
Exponential Functions
47
The graphs of members of the family of functions y − b x are shown in Figure 3 for
various values of the base b. Notice that all of these graphs pass through the same point
s0, 1d because b 0 − 1 for b ± 0. Notice also that as the base b gets larger, the exponential
function grows more rapidly (for x . 0).
” 4 ’®
” 2 ’®
1
1
y
10®
4®
2®
If 0 , b , 1, then b x approaches 0
as x becomes large. If b . 1, then b x
approaches 0 as x decreases through
negative values. In both cases the
x-axis is a horizontal asymptote. These
matters are discussed in Section 2.6.
1.5®
1®
0
FIGURE 3
1
x
You can see from Figure 3 that there are basically three kinds of exponential functions
y − b x. If 0 , b , 1, the exponential function decreases; if b − 1, it is a constant; and
if b . 1, it increases. These three cases are illustrated in Figure 4. Observe that if b ± 1,
then the exponential function y − b x has domain R and range s0, `d. Notice also that,
since s1ybd x − 1yb x − b 2x, the graph of y − s1ybd x is just the reflection of the graph of
y − b x about the y-axis.
y
1
(0, 1)
0
FIGURE 4
y
y
(a) y=b ®, 0<b<1
x
0
(b) y=1®
(0, 1)
x
0
x
(c) y=b ®, b>1
One reason for the importance of the exponential function lies in the following properties. If x and y are rational numbers, then these laws are well known from elementary
algebra. It can be proved that they remain true for arbitrary real numbers x and y.
www.StewartCalculus.com
For review and practice using the
Laws of Exponents, click on Review
of Algebra.
Laws of Exponents If a and b are positive numbers and x and y are any real
numbers, then
bx
1. b x1y − b x b y
2. b x2y − y
3. sb x d y − b xy
4. sabd x − a xb x
b
EXAMPLE 1 Sketch the graph of the function y − 3 2 2 x and determine its domain
and range.
For a review of reflecting and shifting
graphs, see Section 1.3.
SOLUTION First we reflect the graph of y − 2 x [shown in Figures 2 and 5(a)] about the
x-axis to get the graph of y − 22 x in Figure 5(b). Then we shift the graph of y − 22 x
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
48
CHAPTER 1
Functions and Models
upward 3 units to obtain the graph of y − 3 2 2 x in Figure 5(c). The domain is R and
the range is s2`, 3d.
y
y
y
y=3
2
1
0
0
x
x
0
x
_1
(a) y=2®
FIGURE 5
(b) y=_2®
(c) y=3-2®
n
EXAMPLE 2 Use a graphing calculator or computer to compare the exponential
function f sxd − 2 x and the power function tsxd − x 2. Which function grows more
quickly when x is large?
Example 2 shows that y − 2 x increases
more quickly than y − x 2. To demonstrate just how quickly f sxd − 2 x
increases, let’s perform the following
thought experiment. Suppose we start
with a piece of paper a thousandth of
an inch thick and we fold it in half
50 times. Each time we fold the paper
in half, the thickness of the paper
doubles, so the thickness of the resulting paper would be 250y1000 inches.
How thick do you think that is? It
works out to be more than 17 million
miles!
SOLUTION Figure 6 shows both functions graphed in the viewing rectangle f22, 6g
by f0, 40g. We see that the graphs intersect three times, but for x . 4 the graph of
f sxd − 2 x stays above the graph of tsxd − x 2. Figure 7 gives a more global view and
shows that for large values of x, the exponential function f sxd − 2 x grows far more
rapidly than the power function tsxd − x 2.
40
y=2®
y=≈
250
y=2®
y=≈
_2
0
FIGURE 6
6
0
FIGURE 7
8
n
■ Applications of Exponential Functions
The exponential function occurs very frequently in mathematical models of nature and
society. Here we indicate briefly how it arises in the description of increasing population
or decreasing viral loads. In later chapters we will pursue these and other applications in
greater detail.
First we consider a population of bacteria in a homogeneous nutrient medium. Suppose that by sampling the population at certain intervals, it is determined that the population doubles every hour. If the number of bacteria at time t is pstd, where t is measured in
hours, and the initial population is ps0d − 1000, then we have
ps1d − 2ps0d − 2 3 1000
ps2d − 2ps1d − 2 2 3 1000
ps3d − 2ps2d − 2 3 3 1000
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.4
49
Exponential Functions
It seems from this pattern that, in general,
pstd − 2 t 3 1000 − s1000d2 t
This population function is a constant multiple of the exponential function y − 2 t, so it
exhibits the rapid growth that we observed in Figure 7. Under ideal conditions (unlimited
space and nutrition and absence of disease) this exponential growth is typical of what
actually occurs in nature.
Table 1 World Population
t
(years since 1900)
Population P
(millions)
0
10
20
30
40
50
60
70
80
90
100
110
1650
1750
1860
2070
2300
2560
3040
3710
4450
5280
6080
6870
EXAMPLE 3 Table 1 shows data for the population of the world in the 20th century
and Figure 8 shows the corresponding scatter plot.
The pattern of the data points in Figure 8 suggests exponential growth, so we use a
graphing calculator (or computer) with exponential regression capability to apply the
method of least squares and obtain the exponential model
Pstd − s1.43653 3 109 d ! s1.01395d t
where t − 0 corresponds to 1900. Figure 9 shows the graph of this exponential function
together with the original data points. We see that the exponential curve fits the data
reasonably well. The period of relatively slow population growth is explained by the
two world wars and the Great Depression of the 1930s.
P
P
5x10'
5x10'
0
20
40
60
80
100
Years since 1900
FIGURE 8 Scatter plot for world population growth
Table 2
t (days)
Vstd
1
4
8
11
15
22
76.0
53.0
18.0
9.4
5.2
3.6
120
t
0
20
40
60
80
100
120
t
Years since 1900
FIGURE 9 Exponential model for world population growth
EXAMPLE 4 In 1995 a research article was published that detailed the effect of the
protease inhibitor ABT-538 on the human immunodeficiency virus HIV-1.1 Table 2
shows values of the plasma viral load Vstd of patient 303, measured in RNA copies
per mL, t days after ABT-538 treatment was begun. The corresponding scatter plot is
shown in Figure 10 (on the following page).
The rather dramatic decline of the viral load that we see in Figure 10 reminds us of
the graphs of the exponential function y − b x in Figures 3 and 4(a) for the case where
the base b is less than 1. So let’s model the function Vstd by an exponential function.
Using a graphing calculator or computer to fit the data in Table 2 with an exponential
1. D. Ho et al., “Rapid Turnover of Plasma Virions and CD4 Lymphocytes in HIV-1 Infection,” Nature 373
(1995): 123–26.
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n
CHAPTER 1
Functions and Models
function of the form y − a ? b t, we obtain the model
V − 96.39785 ? s0.818656dt
In Figure 11 we graph this exponential function with the data points and observe
that the model represents the viral load reasonably well for the first month
of treatment.
V
V
60
60
RNA copies / mL
RNA copies / mL
50
40
20
0
10
20
30
t (days)
40
20
0
10
20
30
FIGURE 10
FIGURE 11
Plasma viral load in patient 303
Exponential model for viral load
t (days)
n
In Example 3 we used an exponential function of the form y − a ! b t, b . 1, to model
an increasing population and in Example 4 we used y − a ! b t, b , 1, to model a decreasing viral load. In Section 3.8 we will explore additional examples of quantities that grow
or decline exponentially, including the value of an investment account with compounding
interest and the amount of radioactive material that remains as the material decays.
■ The Number e
Of all possible bases for an exponential function, there is one that is most convenient
for the purposes of calculus. The choice of a base b is influenced by the way the graph
of y − b x crosses the y-axis. Figures 12 and 13 show the tangent lines to the graphs
of y − 2 x and y − 3 x at the point s0, 1d. (Tangent lines will be defined precisely in
Section 2.7. For present purposes, you can think of the tangent line to an exponential
graph at a point as the line that touches the graph only at that point.) If we measure
the slopes of these tangent lines at s0, 1d, we find that m < 0.7 for y − 2 x and m < 1.1
for y − 3 x.
It turns out, as we will see in Chapter 3, that some of the formulas of calculus will be
greatly simplified if we choose the base b so that the slope of the tangent line to y − b x
at s0, 1d is exactly 1. (See Figure 14.) In fact, there is such a number and it is denoted
by the letter e. (This notation was chosen by the Swiss mathematician Leonhard Euler
in 1727, probably because it is the first letter of the word exponential.) In view of
y
1
0
FIGURE 12
y
y=2®
y
y=3®
m=1
mÅ1.1
mÅ0.7
1
0
x
FIGURE 13
y=´
1
x
0
x
FIGURE 14
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SECTION 1.4
Exponential Functions
51
Figures 12 and 13, it comes as no surprise that the number e lies between 2 and 3 and the
graph of y − e x lies between the graphs of y − 2 x and y − 3 x. (See Figure 15.) In
Chapter 3 we will see that the value of e, correct to five decimal places, is
e < 2.71828
We call the function f sxd − e x the natural exponential function.
y
y=3®
y=2®
y=e ®
1
FIGURE 15
The graph of y − e x lies between the
graphs of y − 2 x and y − 3 x.
x
0
EXAMPLE 5 Graph the function y − 12 e2x 2 1 and state the domain and range.
SOLUTION We start with the graph of y − e x from Figures 14 and 16(a) and reflect
about the y-axis to get the graph of y − e2x in Figure 16(b). (Notice that the tangent
line to the graph at the y-intercept has slope 21.) Then we compress the graph vertically by a factor of 2 to obtain the graph of y − 12 e2x in Figure 16(c). Finally, we shift
the graph downward one unit to get the desired graph in Figure 16(d). The domain is R
and the range is s21, `d.
y
1
0
y
y
y
1
1
1
0
x
(a) y=´
(b) y=e–®
x
0
(c) y= 21 e–®
x
y=_1
0
x
(d) y= 21 e–®-1
FIGURE 16
n
How far to the right do you think we would have to go for the height of the graph of
y − e x to exceed a million? The next example demonstrates the rapid growth of this
function by providing an answer that might surprise you.
1.5x10^
y=10^
EXAMPLE 6 Use a graphing calculator or computer to find the values of x for which
e x . 1,000,000.
y=´
0
FIGURE 17
15
SOLUTION In Figure 17 we graph both the function y − e x and the horizontal line
y − 1,000,000. We see that these curves intersect when x < 13.8. So e x . 10 6 when
x . 13.8. It is perhaps surprising that the values of the exponential function have
already surpassed a million when x is only 14.
n
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52
CHAPTER 1
Functions and Models
1.4
Exercises
1–2 Use the Laws of Exponents to rewrite and simplify each
expression.
1. (a)
226
43
(b)
s23d6
96
(c)
(d)
x3 ! xn
x n11
(e) b 3 s3b21d22
(f )
s4
s108
(b) 27 2y3
1
4
x5
s
2x 2 y
s3x 22 yd 2
16. Starting with the graph of y − e x, find the equation of the
graph that results from
(a) reflecting about the line y − 4.
(b) reflecting about the line x − 2.
17–18 Find the domain of each function.
2
17. (a) f sxd −
3
2. (a)
3
(d) s2x 22 d23x 23
(e)
(c) 2x 2 s3x 5d2
3a 3y2 ! a 1y2
a 21
3
ab
s
4. (a) How is the number e defined?
(b) What is an approximate value for e ?
(c) What is the natural exponential function?
y − 5 x,
y − 20 x
6. y − e x,
y − e 2x,
y − 8 x,
y − 8 2x
7. y − 3 x,
y − 10 x,
y − ( 13 ) , y − ( 101 )
8. y − 0.9 x,
y − 0.6 x,
x
y − 0.3 x,
18. (a) tstd − s10 t 2 100
11x
e cos x
(b) tstd − sinse t 2 1d
19–20 Find the exponential function f sxd − Cb x whose graph
is given.
19.
20.
y
y
(3, 24)
(_1, 3)
4
”1, 3 ’
(1, 6)
0
x
x
0
21. If f sxd − 5 x, show that
; 5–8 Graph the given functions on a common screen. How are
these graphs related?
y − e x,
(b) f sxd −
sa sb
(f )
3. (a) Write an equation that defines the exponential function
with base b . 0.
(b) What is the domain of this function?
(c) If b ± 1, what is the range of this function?
(d) Sketch the general shape of the graph of the exponential
function for each of the following cases.
(i) b . 1
(ii) b − 1
(iii) 0 , b , 1
5. y − 2 x,
1 2 ex
2
1 2 e12x
S D
5h 2 1
f sx 1 hd 2 f sxd
− 5x
h
h
22. Suppose you are offered a job that lasts one month. Which
of the following methods of payment do you prefer?
I. One million dollars at the end of the month.
II. One cent on the first day of the month, two cents on the
second day, four cents on the third day, and, in general,
2 n21 cents on the nth day.
x
y − 0.1x
9–14 Make a rough sketch by hand of the graph of the function.
Use the graphs given in Figures 3 and 15 and, if necessary, the
transformations of Section 1.3.
9. tsxd − 3 x 1 1
10. hsxd − 2 ( 12 ) 2 3
11. y − 2e2x
12. y − 4 x12
13. y − 1 2 12 e2x
14. y − e | x |
x
15. Starting with the graph of y − e x, write the equation of the
graph that results from
(a) shifting 2 units downward.
(b) shifting 2 units to the right.
(c) reflecting about the x-axis.
(d) reflecting about the y-axis.
(e) reflecting about the x-axis and then about the y-axis.
23. Suppose the graphs of f sxd − x 2 and tsxd − 2 x are drawn
on a coordinate grid where the unit of measurement is
1 inch. Show that at a distance 2 ft to the right of the origin,
the height of the graph of f is 48 ft but the height of the
graph of t is about 265 mi.
; 24. Compare the functions f sxd − x and tsxd − 5 by graphing both functions in several viewing rectangles. Find all
points of intersection of the graphs correct to one decimal
place. Which function grows more rapidly when x is large?
5
x
; 25. Compare the functions f sxd − x and tsxd − e by graphing both functions in several viewing rectangles. When does
the graph of t finally surpass the graph of f ?
10
x
; 26. Use a graph to estimate the values of x such that
e x . 1,000,000,000.
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.4
27. A researcher is trying to determine the doubling time for a
population of the bacterium Giardia lamblia. He starts a
culture in a nutrient solution and estimates the bacteria
count every four hours. His data are shown in the table.
Time (hours)
0
4
8
12
16
20
24
Bacteria count
sCFUymLd
37
47
63
78
105 130 173
Sebastian Kaulitzki / Shutterstock.com
(a) Make a scatter plot of the data.
(b) Use a calculator or computer to find an exponential
curve f std − a ? b t that models the bacteria population
t hours later.
(c) Graph the model from part (b) together with the scatter
plot in part (a). Use the graph to estimate how long it
takes for the bacteria count to double.
G. lamblia
28. The table gives the population of the United States, in millions, for the years 1900 –2010. Use a graphing calculator
(or computer) with exponential regression capability to
model the US population since 1900. Use the model to
estimate the population in 1925 and to predict the population in the year 2020.
Population
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
76
92
106
123
131
150
179
203
227
250
281
310
53
29. A bacteria culture starts with 500 bacteria and doubles in
size every half hour.
(a) How many bacteria are there after 3 hours?
(b) How many bacteria are there after t hours?
(c) How many bacteria are there after 40 minutes?
(d) Graph the population function and estimate the time
;
for the population to reach 100,000.
30. A gray squirrel population was introduced in a certain
region 18 years ago. Biologists observe that the population doubles every six years, and now the population
is 600.
(a) What was the initial squirrel population?
(b) What is the expected squirrel population t years after
introduction?
(c) Estimate the expected squirrel population 10 years
from now.
31. In Example 4, the patient’s viral load V was 76.0 RNA
copies per mL after one day of treatment. Use the graph
of V in Figure 11 to estimate the additional time required
for the viral load to decrease to half that amount.
32. After alcohol is fully absorbed into the body, it is metabolized. Suppose that after consuming several alcoholic drinks
earlier in the evening, your blood alcohol concentration
(BAC) at midnight is 0.14 gydL. After 1.5 hours your BAC
is half this amount.
(a) Find an exponential model for your BAC t hours after
midnight.
(b) Graph your BAC and use the graph to determine when
;
your BAC reaches the legal limit of 0.08 gydL.
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of Ethanol after
Oral Administration in the Fasting State,” Journal of Pharmacokinetics and
Biopharmaceutics 5 (1977): 207–24.
; 33. If you graph the function
f sxd −
Year
Exponential Functions
1 2 e 1yx
1 1 e 1yx
you’ll see that f appears to be an odd function. Prove it.
; 34. Graph several members of the family of functions
f sxd −
1
1 1 ae bx
where a . 0. How does the graph change when b changes?
How does it change when a changes?
; 35. Graph several members of the family of functions
f sxd −
a xya
(e 1 e2xya)
2
where a . 0. How does the graph change as a increases?
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54
CHAPTER 1
Functions and Models
1.5 Inverse Functions and Logarithms
■ Inverse Functions
Table 1 gives data from an experiment in which a biologist started a bacteria culture with
100 bacteria in a limited nutrient medium; the size of the bacteria population was recorded
at hourly intervals. The number of bacteria N is a function of the time t: N − f std.
Suppose, however, that the biologist changes her point of view and becomes interested in the time required for the population to reach various levels. In other words, she
is thinking of t as a function of N. This function is called the inverse function of f,
denoted by f 21, and read “ f inverse.” Here t − f 21sNd is the time required for the population level to reach N. The values of f 21 can be found by reading Table 1 from right to
left or by consulting Table 2. For instance, f 21s550d − 6 because f s6d − 550.
Table 2 t as a function of N
Table 1 N as a function of t
4
10
3
7
2
4
1
2
f
4
10
3
4
2
1
2
g
but
In the language of inputs and outputs,
Definition 1 says that f is one-to-one
if each output corresponds to only
one input.
y
y=ƒ
⁄
N
t − f 21 sNd
− time to reach N bacteria
0
1
2
3
4
5
6
7
8
100
168
259
358
445
509
550
573
586
100
168
259
358
445
509
550
573
586
0
1
2
3
4
5
6
7
8
ts2d − ts3d
f is one-to-one; t is not.
0
N − f std
− population at time t
Not all functions possess inverses. Let’s compare the functions f and t whose arrow
diagrams are shown in Figure 1. Note that f never takes on the same value twice (any two
inputs in A have different outputs), whereas t does take on the same value twice (both 2
and 3 have the same output, 4). In symbols,
FIGURE 1
fl
t (hours)
‡
¤
FIGURE 2
This function is not one-to-one
because f sx 1 d − f sx 2 d.
x
f sx 1 d ± f sx 2 d
whenever x 1 ± x 2
Functions that share this property with f are called one-to-one functions.
1 Definition A function f is called a one-to-one function if it never takes on
the same value twice; that is,
f sx 1 d ± f sx 2 d
whenever x 1 ± x 2
If a horizontal line intersects the graph of f in more than one point, then we see from
Figure 2 that there are numbers x 1 and x 2 such that f sx 1 d − f sx 2 d. This means that f is
not one-to-one.
Therefore we have the following geometric method for determining whether a function is one-to-one.
Horizontal Line Test A function is one-to-one if and only if no horizontal line
intersects its graph more than once.
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SECTION 1.5
Inverse Functions and Logarithms
55
EXAMPLE 1 Is the function f sxd − x 3 one-to-one?
SOLUTION 1 If x 1 ± x 2, then x13 ± x 23 (two different numbers can’t have the same
cube). Therefore, by Definition 1, f sxd − x 3 is one-to-one.
SOLUTION 2 From Figure 3 we see that no horizontal line intersects the graph of
f sxd − x 3 more than once. Therefore, by the Horizontal Line Test, f is one-to-one.
y
y=˛
x
0
FIGURE 3
f sxd − x 3 is one-to-one.
n
EXAMPLE 2 Is the function tsxd − x 2 one-to-one?
y
SOLUTION 1 This function is not one-to-one because, for instance,
y=≈
ts1d − 1 − ts21d
and so 1 and 21 have the same output.
x
SOLUTION 2 From Figure 4 we see that there are horizontal lines that intersect the graph
of t more than once. Therefore, by the Horizontal Line Test, t is not one-to-one.
n
tsxd − x 2 is not one-to-one.
One-to-one functions are important because they are precisely the functions that possess inverse functions according to the following definition.
0
FIGURE 4
2 Definition Let f be a one-to-one function with domain A and range B.
Then its inverse function f 21 has domain B and range A and is defined by
f 21syd − x
&?
f sxd − y
for any y in B.
x
A
f
B
f –!
y
FIGURE 5
This definition says that if f maps x into y, then f 21 maps y back into x. (If f were not
one-to-one, then f 21 would not be uniquely defined.) The arrow diagram in Figure 5
indicates that f 21 reverses the effect of f. Note that
domain of f 21 − range of f
range of f 21 − domain of f
For example, the inverse function of f sxd − x 3 is f 21sxd − x 1y3 because if y − x 3,
then
f 21syd − f 21sx 3 d − sx 3 d1y3 − x
CAUTION Do not mistake the 21 in f 21 for an exponent. Thus
The reciprocal 1yf sxd could be
written as f f sxdg 21.
f 21sxd does not mean
1
f sxd
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56
CHAPTER 1
Functions and Models
A
B
1
5
3
7
8
_10
EXAMPLE 3 If f is a one-to-one function and f s1d − 5, f s3d − 7, and f s8d − 210,
find f 21s7d, f 21s5d, and f 21s210d.
SOLUTION From the definition of f 21 we have
f 21s7d − 3
because
f s3d − 7
f s5d − 1
because
f s1d − 5
f 21s210d − 8
because
f s8d − 210
21
f
A
B
The diagram in Figure 6 makes it clear how f
1
5
3
7
The letter x is traditionally used as the independent variable, so when we concentrate
on f 21 rather than on f, we usually reverse the roles of x and y in Definition 2 and write
8
_10
f 21sxd − y
3
f –!
FIGURE 6
The inverse function reverses inputs
and outputs.
21
reverses the effect of f in this case.
&?
n
f syd − x
By substituting for y in Definition 2 and substituting for x in (3), we get the following
cancellation equations:
4
f 21s f sxdd − x
for every x in A
f s f 21sxdd − x
for every x in B
The first cancellation equation says that if we start with x, apply f, and then apply f 21,
we arrive back at x, where we started (see the machine diagram in Figure 7). Thus f 21
undoes what f does. The second equation says that f undoes what f 21 does.
FIGURE 7
x
f
ƒ
f –!
x
For example, if f sxd − x 3, then f 21sxd − x 1y3 and so the cancellation equations become
f 21s f sxdd − sx 3 d1y3 − x
f s f 21sxdd − sx 1y3 d3 − x
These equations simply say that the cube function and the cube root function cancel each
other when applied in succession.
Now let’s see how to compute inverse functions. If we have a function y − f sxd and
are able to solve this equation for x in terms of y, then according to Definition 2 we must
have x − f 21syd. If we want to call the independent variable x, we then interchange x and
y and arrive at the equation y − f 21sxd.
5 How to Find the Inverse Function of a One-to-One Function f
STEP 1 Write y − f sxd.
STEP 2 Solve this equation for x in terms of y (if possible).
STEP 3 To express f 21 as a function of x, interchange x and y.
The resulting equation is y − f 21sxd.
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SECTION 1.5
Inverse Functions and Logarithms
57
EXAMPLE 4 Find the inverse function of f sxd − x 3 1 2.
SOLUTION According to (5) we first write
y − x3 1 2
Then we solve this equation for x:
x3 − y 2 2
In Example 4, notice how f 21 reverses
the effect of f . The function f is the
rule “Cube, then add 2”; f 21 is the
rule “Subtract 2, then take the cube
root.”
3
x−s
y22
Finally, we interchange x and y:
3
y−s
x22
3
Therefore the inverse function is f 21sxd − s
x 2 2.
n
The principle of interchanging x and y to find the inverse function also gives us the
method for obtaining the graph of f 21 from the graph of f. Since f sad − b if and only
if f 21sbd − a, the point sa, bd is on the graph of f if and only if the point sb, ad is on the
graph of f 21. But we get the point sb, ad from sa, bd by reflecting about the line y − x.
(See Figure 8.)
y
0
y
(b, a)
f –!
(a, b)
0
x
y=x
y=x
FIGURE 8
FIGURE 9
x
f
Therefore, as illustrated by Figure 9:
The graph of f 21 is obtained by reflecting the graph of f about the line y − x.
y
y=ƒ
EXAMPLE 5 Sketch the graphs of f sxd − s21 2 x and its inverse function using the
same coordinate axes.
y=x
(_1, 0)
0
x
(0, _1)
y=f –!(x)
FIGURE 10
SOLUTION First we sketch the curve y − s21 2 x (the top half of the parabola
y 2 − 21 2 x, or x − 2y 2 2 1) and then we reflect about the line y − x to get the
graph of f 21. (See Figure 10.) As a check on our graph, notice that the expression for
f 21 is f 21sxd − 2x 2 2 1, x > 0. So the graph of f 21 is the right half of the parabola
y − 2x 2 2 1 and this seems reasonable from Figure 10.
n
■ Logarithmic Functions
If b . 0 and b ± 1, the exponential function f sxd − b x is either increasing or decreasing
and so it is one-to-one by the Horizontal Line Test. It therefore has an inverse function
f 21, which is called the logarithmic function with base b and is denoted by log b. If we
use the formulation of an inverse function given by (3),
f 21sxd − y &?
f syd − x
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58
CHAPTER 1
Functions and Models
then we have
log b x − y &? b y − x
6
Thus, if x . 0, then log b x is the exponent to which the base b must be raised to give x.
For example, log10 0.001 − 23 because 1023 − 0.001.
The cancellation equations (4), when applied to the functions f sxd − b x and
21
f sxd − log b x, become
log b sb x d − x for every x [ R
7
y
y=x
y=b®, b>1
0
x
b log x − x for every x . 0
b
The logarithmic function log b has domain s0, `d and range R. Its graph is the reflection of the graph of y − b x about the line y − x.
Figure 11 shows the case where b . 1. (The most important logarithmic functions have
base b . 1.) The fact that y − b x is a very rapidly increasing function for x . 0 is
reflected in the fact that y − log b x is a very slowly increasing function for x . 1.
Figure 12 shows the graphs of y − log b x with various values of the base b . 1.
Because log b 1 − 0, the graphs of all logarithmic functions pass through the point s1, 0d.
y
y=log b x, b>1
y=log™ x
y=log£ x
1
FIGURE 11
0
x
1
y=log¡¸ x
y=log∞ x
FIGURE 12
The following properties of logarithmic functions follow from the corresponding
properties of exponential functions given in Section 1.4.
Laws of Logarithms If x and y are positive numbers, then
1. log b sxyd − log b x 1 log b y
2. log b
SD
x
y
− log b x 2 log b y
3. log b sx r d − r log b x
(where r is any real number)
EXAMPLE 6 Use the laws of logarithms to evaluate log 2 80 2 log 2 5.
SOLUTION Using Law 2, we have
log 2 80 2 log 2 5 − log 2
because 2 4 − 16.
S D
80
5
− log 2 16 − 4
n
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SECTION 1.5
Inverse Functions and Logarithms
59
■ Natural Logarithms
Notation for Logarithms
Most textbooks in calculus and the
sciences, as well as calculators,
use the notation ln x for the natural
logarithm and log x for the “common
logarithm,” log10 x. In the more
advanced mathematical and scientific
literature and in computer languages,
however, the notation log x usually
denotes the natural logarithm.
Of all possible bases b for logarithms, we will see in Chapter 3 that the most convenient
choice of a base is the number e, which was defined in Section 1.4. The logarithm with
base e is called the natural logarithm and has a special notation:
log e x − ln x
If we set b − e and replace log e with “ln” in (6) and (7), then the defining properties
of the natural logarithm function become
8
9
ln x − y
&? e y − x
lnse x d − x
x[R
ln x
x.0
e
−x
In particular, if we set x − 1, we get
ln e − 1
Combining Property 9 with Law 3 allows us to write
r
x r − e ln sx d − e r ln x
x.0
Thus a power of x can be expressed in an equivalent exponential form; we will find this
useful in the chapters to come.
x r − e r ln x
10
EXAMPLE 7 Find x if ln x − 5.
SOLUTION 1 From (8) we see that
ln x − 5
means
e5 − x
Therefore x − e 5.
(If you have trouble working with the “ln” notation, just replace it by log e . Then the
equation becomes log e x − 5; so, by the definition of logarithm, e 5 − x.)
SOLUTION 2 Start with the equation
ln x − 5
and apply the exponential function to both sides of the equation:
e ln x − e 5
But the second cancellation equation in (9) says that e ln x − x. Therefore x − e 5.
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n
60
CHAPTER 1
Functions and Models
EXAMPLE 8 Solve the equation e 523x − 10.
SOLUTION We take natural logarithms of both sides of the equation and use (9):
lnse 523x d − ln 10
5 2 3x − ln 10
3x − 5 2 ln 10
x − 13 s5 2 ln 10d
Using a calculator, we can approximate the solution: to four decimal places, x < 0.8991.
n
The laws of logarithms allow us to expand logarithms of products and quotients as
sums and differences of logarithms. These same laws also allow us to combine sums and
differences of logarithms into a single logarithmic expression. These processes are illustrated in Examples 9 and 10.
EXAMPLE 9 Use the laws of logarithms to expand ln
x 2sx 2 1 2
.
3x 1 1
SOLUTION Using Laws 1, 2, and 3 of logarithms, we have
ln
x 2sx 2 1 2
− ln x 2 1 ln sx 2 1 2 2 lns3x 1 1d
3x 1 1
− 2 ln x 1 12 lnsx 2 1 2d 2 lns3x 1 1d
n
EXAMPLE 10 Express ln a 1 12 ln b as a single logarithm.
SOLUTION Using Laws 3 and 1 of logarithms, we have
ln a 1 12 ln b − ln a 1 ln b 1y2
− ln a 1 lnsb
− ln ( asb )
n
The following formula shows that logarithms with any base can be expressed in terms
of the natural logarithm.
11 Change of Base Formula For any positive number b sb ± 1d, we have
log b x −
ln x
ln b
PROOF Let y − log b x. Then, from (6), we have b y − x. Taking natural logarithms of
both sides of this equation, we get y ln b − ln x. Therefore
y−
ln x
ln b
n
Formula 11 enables us to use a calculator to compute a logarithm with any base (as
shown in the following example). Similarly, Formula 11 allows us to graph any logarithmic function on a graphing calculator or computer (see Exercises 49 and 50).
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SECTION 1.5
y
y=´
EXAMPLE 11 Evaluate log 8 5 correct to six decimal places.
SOLUTION Formula 11 gives
y=x
log 8 5 −
1
y=ln x
0
x
1
FIGURE 13
The graph of y − ln x is the reflection of the graph of y − e x about the
line y − x.
n
The graphs of the exponential function y − e x and its inverse function, the natural logarithm function, are shown in Figure 13. In common with all other logarithmic functions
with base greater than 1, the natural logarithm is an increasing function defined on s0, `d
and the y-axis is a vertical asymptote. (This means that the values of ln x become very
large negative as x approaches 0.)
EXAMPLE 12 Sketch the graph of the function y − lnsx 2 2d 2 1.
SOLUTION We start with the graph of y − ln x as given in Figure 13. Using the transformations of Section 1.3, we shift it 2 units to the right to get the graph of y − lnsx 2 2d and
then we shift it 1 unit downward to get the graph of y − lnsx 2 2d 2 1. (See Figure 14.)
y
y
x=2
y=ln x
(1, 0)
ln 5
< 0.773976
ln 8
■ Graph and Growth of the Natural Logarithm
y
0
61
Inverse Functions and Logarithms
x=2
y=ln(x-2)-1
y=ln(x-2)
0
x
2
x
(3, 0)
0
2
x
(3, _1)
FIGURE 14
n
Although ln x is an increasing function, it grows very slowly when x . 1. In fact, ln x
grows more slowly than any positive power of x. To illustrate this fact, we graph y − ln x
and y − x 1y2 − sx in Figures 15 and 16. You can see that the graphs initially grow at
comparable rates, but eventually the root function far surpasses the logarithm.
y
y
20
x
y=œ„
1
0
y=ln x
y=ln x
1
x
y=œ„
x
FIGURE 15
0
1000 x
FIGURE 16
■ Inverse Trigonometric Functions
When we try to find the inverse trigonometric functions, we have a slight difficulty:
because the trigonometric functions are not one-to-one, they don’t have inverse functions. The difficulty is overcome by restricting the domains of these functions so that
they become one-to-one.
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62
CHAPTER 1
Functions and Models
You can see from Figure 17 that the sine function y − sin x is not one-to-one (use the
Horizontal Line Test). However, if we restrict the domain to the interval f2!y2, !y2!,
then the function is one-to-one and all values in the range of y − sin x are attained (see
Figure 18). The inverse function of this restricted sine function f exists and is denoted by
sin 21 or arcsin. It is called the inverse sine function or the arcsine function.
y
0
_π
y
y=sin x
π
2
_ π2
0
x
π
π
2
x
FIGURE 18
FIGURE 17
y − sin x, 2!2 < x < !2
Since the definition of an inverse function says that
f 21sxd − y &?
f s yd − x
sin21x − y &? sin y − x
and 2
we have
sin21x ±
1
sin x
!
!
<y<
2
2
So, if 21 < x < 1, sin 21x is the number between 2!y2 and !y2 whose sine is x.
EXAMPLE 13 Evaluate (a) sin21( 12 ) and (b) tan (arcsin 13 ).
SOLUTION
(a) We have
sin21( 12 ) −
3
¨
1
2
2 œ„
FIGURE 19
!
6
because sins!y6d − 12 and !y6 lies between 2!y2 and !y2.
(b) Let " − arcsin 13 , so sin " − 13 . Then we can draw a right triangle with angle " as
in Figure 19 and deduce from the Pythagorean Theorem that the third side has length
s9 2 1 − 2s2 . This enables us to read from the triangle that
tan (arcsin 13 ) − tan u −
y
2s2
n
The cancellation equations for inverse functions become, in this case,
π
2
0
_1
1
1
_ π2
FIGURE 20
y − sin21 x − arcsin x
x
!
!
<x<
2
2
sin21ssin xd − x
for 2
sinssin21xd − x
for 21 < x < 1
The inverse sine function, sin21, has domain f21, 1g and range f2!y2, !y2g, and
its graph, shown in Figure 20, is obtained from that of the restricted sine function (Figure 18) by reflection about the line y − x.
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SECTION 1.5
y
Inverse Functions and Logarithms
63
The inverse cosine function is handled similarly. The restricted cosine function
f sxd − cos x, 0 < x < !, is one-to-one (see Figure 21) and so it has an inverse function
denoted by cos 21 or arccos.
1
0
π
2
π
x
cos21x − y &? cos y − x
and 0 < y < !
The cancellation equations are
FIGURE 21
y − cos x, 0 < x < !
cos 21scos xd − x
for 0 < x < !
cosscos21xd − x
for 21 < x < 1
y
π
The inverse cosine function, cos21, has domain f21, 1g and range f0, !g. Its graph is
shown in Figure 22.
The tangent function can be made one-to-one by restricting it to the interval
s2!y2, !y2d. Thus the inverse tangent function is defined as the inverse of the function f sxd − tan x, 2!y2 , x , !y2. (See Figure 23.) It is denoted by tan21 or arctan.
π
2
0
_1
x
1
FIGURE 22
tan21x − y &? tan y − x
and 2
y − cos21 x − arccos x
y
!
!
,y,
2
2
EXAMPLE 14 Simplify the expression cosstan21xd.
SOLUTION 1 Let y − tan21x. Then tan y − x and 2!y2 , y , !y2. We want to find
cos y but, since tan y is known, it is easier to find sec y first:
_ π2
π
2
0
sec2 y − 1 1 tan2 y − 1 1 x 2
x
sec y − s1 1 x 2
Thus
y − tan x, 2!2 , x , !2
y
cosstan21xd − cos y −
1
1
−
sec y
s1 1 x 2
SOLUTION 2 Instead of using trigonometric identities as in Solution 1, it is perhaps
easier to use a diagram. If y − tan21x, then tan y − x, and we can read from Figure 24
(which illustrates the case y . 0) that
FIGURE 23
œ„„„„„
1+≈
ssince sec y . 0 for 2!y2 , y , !y2d
x
cosstan21xd − cos y −
1
n
s1 1 x 2
The inverse tangent function, tan21 − arctan, has domain R and range s2!y2, !y2d.
Its graph is shown in Figure 25.
1
y
FIGURE 24
π
2
0
FIGURE 25
y − tan21 x − arctan x
x
_ π2
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64
CHAPTER 1
Functions and Models
We know that the lines x − 6!y2 are vertical asymptotes of the graph of tan. Since
the graph of tan21 is obtained by reflecting the graph of the restricted tangent function
about the line y − x, it follows that the lines y − !y2 and y − 2!y2 are horizontal
asymptotes of the graph of tan 21.
The remaining inverse trigonometric functions are not used as frequently and are summarized here.
y
and y [ s0, !y2g ø s!, 3!y2g
| |
y − sec x (| x | > 1) &? sec y − x and y [ f0, !y2d ø f!, 3!y2d
y − csc21x ( x > 1) &? csc y − x
12
21
_1
0
π
y − cot21x sx [ Rd
x
2π
&? cot y − x
y [ s0, !d
and
The choice of intervals for y in the definitions of csc21 and sec21 is not universally
agreed upon. For instance, some authors use y [ f0, !y2d ø s!y2, !g in the definition
of sec21. [You can see from the graph of the secant function in Figure 26 that both this
choice and the one in (12) will work.]
FIGURE 26
y − sec x
1.5 Exercises
1. (a) What is a one-to-one function?
(b) How can you tell from the graph of a function whether it
is one-to-one?
2. (a) Suppose f is a one-to-one function with domain A and
range B. How is the inverse function f 21 defined? What
is the domain of f 21 ? What is the range of f 21 ?
(b) If you are given a formula for f, how do you find a
formula for f 21 ?
(c) If you are given the graph of f, how do you find the graph
of f 21 ?
3–16 A function is given by a table of values, a graph, a formula,
or a verbal description. Determine whether it is one-to-one.
3.
4.
x
1
2
3
4
5
6
f sxd
1.5
2.0
3.6
5.3
2.8
2.0
x
1
2
3
4
5
6
1.0
1.9
2.8
3.5
3.1 y
2.9
f sxd
y
y
5.
6.
y
x
y
y
x
11. r std − t 3 1 4
3
12. tsxd − s
x
13. tsxd − 1 2 sin x
14. f sxd − x 4 2 1, 0 ⩽ x ⩽ 10
15. f std is the height of a football t seconds after kickoff.
16. f std is your height at age t.
17. Assume that f is a one-to-one function.
(a) If f s6d − 17, what is f 21s17d?
(b) If f 21s3d − 2, what is f s2d?
18. If f sxd − x 5 1 x 3 1 x, find f 21s3d and f s f 21s2dd.
20. The graph of f is given.
(a) Why is f one-to-one?
(b) What are the domain and range of f 21 ?
(c) What is the value of f 21s2d?
(d) Estimate the value of f 21s0d.
y
x
x
1
0
8.
x
10. f sxd − x 4 2 16
19. If tsxd − 3 1 x 1 e x, find t21s4d.
x
7.
9. f sxd − 2x 2 3
1
x
y
y
x
x
21. The formula C − 59 sF 2 32d, where F > 2459.67, expresses
the Celsius temperature C as a function of the Fahrenheit
temperature F. Find a formula for the inverse function and
interpret it. What is the domain of the inverse function?
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SECTION 1.5
22. In the theory of relativity, the mass of a particle with speed v
is
m0
m − f sv d −
s1 2 v 2yc 2
where m 0 is the rest mass of the particle and c is the speed of
light in a vacuum. Find the inverse function of f and explain
its meaning.
23–30 Find a formula for the inverse of the function.
23. f sxd − 1 2 x ,
2
x>0
24. tsxd − x 2 2 x,
2
6 2 3x
5x 1 7
25. tsxd − 2 1 sx 1 1
26. hsxd −
27. y − e 12x
28. y − 3 lnsx 2 2d
3
29. y − (2 1 s
x)
x>1
30. y −
33.
34.
y
1
1
0
1
0
1
0
1
x
x
y
1
0
2
2
1
e2
1
(b) log3 ( 81
)
(c) log 9 3
(b) ln se
(c) ln(ln e e
50
)
41. (a) log 2 30 2 log 2 15
(b) log 3 10 2 log 3 5 2 log 3 18
(c) 2 log 5 100 2 4 log 5 50
42. (a) e 3 ln 2
44. (a) ln
32. f sxd − 1 1 e2x
y
40. (a) ln
Î
12e
1 1 e2x
33–34 Use the given graph of f to sketch the graph of f 21.
y
39. (a) log3 81
3
(c) e ln sln e d
(b) e22 ln 5
x
S
43. (a) log10 sx 2 y 3zd
21
; 31–32 Find an explicit formula for f and use it to graph
21
f , f, and the line y − x on the same screen. To check your
work, see whether the graphs of f and f 21 are reflections about
the line.
31. f sxd − s4 x 1 3
39–42 Find the exact value of each expression.
43–44 Use the laws of logarithms to expand each expression.
2x
5
65
Inverse Functions and Logarithms
x
3x
x23
3
36. Let tsxd − s
1 2 x3 .
21
(a) Find t . How is it related to t ?
(b) Graph t. How do you explain your answer to part (a)?
;
37. (a) How is the logarithmic function y − log b x defined?
(b) What is the domain of this function?
(c) What is the range of this function?
(d) Sketch the general shape of the graph of the function
y − log b x if b . 1.
38. (a) What is the natural logarithm?
(b) What is the common logarithm?
(c) Sketch the graphs of the natural logarithm function
and the natural exponential function with a common
set of axes.
x4
sx 2 2 4
D
(b) log 2 fsx 3 1 1d ssx 2 3d2 g
3
45–46 Express as a single logarithm.
45. (a) log 10 20 2 13 log 10 1000
(b) ln a 2 2 ln b 1 3 ln c
2
46. (a) 3 lnsx 2 2d 2 lnsx 2 5x 1 6d 1 2 lnsx 2 3d
(b) c log a x 2 d log a y 1 log a z
47–48 Use Formula 11 to evaluate each logarithm correct to six
decimal places.
47. (a) log 5 10
(b) log15 12
48. (a) log3 12
(b) log12 6
; 49–50 Use Formula 11 to graph the given functions on a
common screen. How are these graphs related?
49. y − log 1.5 x,
35. Let f sxd − s1 2 x 2 , 0 < x < 1.
(a) Find f 21. How is it related to f ?
(b) Identify the graph of f and explain your answer to
part (a).
(b) ln
50. y − ln x,
y − ln x,
y − log 8 x,
y − log 10 x,
x
y − log 50 x
y − 8x
y−e,
51. Suppose that the graph of y − log 2 x is drawn on a coordinate grid where the unit of measurement is an inch. How
many miles to the right of the origin do we have to move
before the height of the curve reaches 3 ft?
; 52. Compare the functions f sxd − x and tsxd − ln x by graphing both functions in several viewing rectangles. When does
the graph of f finally surpass the graph of t ?
0.1
53–54 Make a rough sketch by hand of the graph of each function. Use the graphs given in Figures 12 and 13 and, if necessary,
the transformations of Section 1.3.
53. (a) y − log 10sx 1 5d
(b) y − 2ln x
54. (a) y − lns2xd
(b) y − ln x
| |
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66
CHAPTER 1
Functions and Models
55–56
(a) What are the domain and range of f ?
(b) What is the x-intercept of the graph of f ?
(c) Sketch the graph of f.
55. f sxd − ln x 1 2
56. f sxd − lnsx 2 1d 2 1
57–60 Solve each equation for x. Give both an exact value and a
decimal approximation, correct to three decimal places.
57. (a) lns4x 1 2d − 3
(b) e 2x23 − 12
58. (a) log 2sx 2 2 x 2 1d − 2
(b) 1 1 e 4x11 − 20
59. (a) ln x 1 lnsx 2 1d − 0
(b) 5 122x − 9
60. (a) lnsln xd − 0
60
(b)
−4
1 1 e2x
fired the capacitors discharge completely and then immediately begin recharging. The charge Q of the capacitors t seconds after the discharge is given by
Qstd − Q 0 s1 2 e2tya d
(The maximum charge capacity is Q 0 and t is measured in
seconds.)
(a) Find a formula for the inverse of this function and
explain its meaning.
(b) How long does it take to recharge the capacitors to 90%
of capacity if a − 50 ?
69–74 Find the exact value of each expression.
69. (a) cos21 s21d
(b) sin21s0.5d
70. (a) tan21 s3
(b) arctans21d
71. (a) csc s2
(b) arcsin 1
21
61. (a) ln x , 0
(b) e x . 5
(21ys2 )
21
73. (a) cot (2s3 )
62. (a) 1 , e 3x21 , 2
(b) 1 2 2 ln x , 3
74. (a) arcsinssins5!y4dd
61–62 Solve each inequality for x.
72. (a) sin
21
63. (a) Find the domain of f sxd − lnse x 2 3d.
(b) Find f 21 and its domain.
64. (a) What are the values of e ln 300 and lnse 300 d?
(b) Use your calculator to evaluate e ln 300 and lnse 300 d. What
do you notice? Can you explain why the calculator has
trouble?
65. Graph the function f sxd − sx 3 1 x 2 1 x 1 1 and explain
why it is one-to-one. Then use a computer algebra system
to find an explicit expression for f 21sxd. (Your CAS will
produce three possible expressions. Explain why two of
them are irrelevant in this context.)
66. (a) If tsxd − x 1 x , x > 0, use a computer algebra system to find an expression for t 21sxd.
(b) Use the expression in part (a) to graph y − tsxd, y − x,
and y − t 21sxd on the same screen.
6
(b) cos21 (s3 y2 )
(b) sec21 2
5
(b) cos (2 sin21 (13
))
75. Prove that cosssin21 xd − s1 2 x 2 .
76–78 Simplify the expression.
76. tanssin21 xd
77. sinstan21 xd
78. sins2 arccos xd
; 79-80 Graph the given functions on the same screen. How are
these graphs related?
79. y − sin x, 2!y2 < x < !y2;
y − sin21x;
y−x
80. y − tan x, 2!y2 , x , !y2;
y − tan x;
y−x
21
4
67. If a bacteria population starts with 100 bacteria and doubles
every three hours, then the number of bacteria after t hours
is n − f std − 100 ∙ 2 ty3.
(a) Find the inverse of this function and explain its meaning.
(b) When will the population reach 50,000 ?
68. The National Ignition Facility at the Lawrence Livermore
National Laboratory maintains the world’s largest laser
facility. The lasers, which are used to start a nuclear fusion
reaction, are powered by a capacitor bank that stores a total
of about 400 megajoules of energy. When the lasers are
81. Find the domain and range of the function
tsxd − sin21s3x 1 1d
; 82. (a) Graph the function f sxd − sinssin xd and explain the
appearance of the graph.
(b) Graph the function tsxd − sin21ssin xd. How do you
explain the appearance of this graph?
21
83. (a) If we shift a curve to the left, what happens to its
reflection about the line y − x? In view of this geometric principle, find an expression for the inverse of
tsxd − f sx 1 cd, where f is a one-to-one function.
(b) Find an expression for the inverse of hsxd − f scxd,
where c ± 0.
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CHAPTER 1
1
Review
67
REVIEW
CONCEPT CHECK
Answers to the Concept Check are available at StewartCalculus.com.
1. (a) What is a function? What are its domain and range?
(b) What is the graph of a function?
(c) How can you tell whether a given curve is the graph of
a function?
9. Suppose that f has domain A and t has domain B.
(a) What is the domain of f 1 t ?
(b) What is the domain of f t ?
(c) What is the domain of fyt ?
2. Discuss four ways of representing a function. Illustrate your
discussion with examples.
10. How is the composite function f 8 t defined? What is its
domain?
3. (a) What is an even function? How can you tell if a function
is even by looking at its graph? Give three examples of an
even function.
(b) What is an odd function? How can you tell if a function
is odd by looking at its graph? Give three examples of
an odd function.
11. Suppose the graph of f is given. Write an equation for each of
the graphs that are obtained from the graph of f as follows.
(a) Shift 2 units upward.
(b) Shift 2 units downward.
(c) Shift 2 units to the right. (d) Shift 2 units to the left.
(e) Reflect about the x-axis.
(f ) Reflect about the y-axis.
(g) Stretch vertically by a factor of 2.
(h) Shrink vertically by a factor of 2.
( i ) Stretch horizontally by a factor of 2.
( j ) Shrink horizontally by a factor of 2.
4. What is an increasing function?
5. What is a mathematical model?
6. Give an example of each type of function.
(a) Linear function
(b) Power function
(c) Exponential function
(d) Quadratic function
(e) Polynomial of degree 5
(f ) Rational function
7. Sketch by hand, on the same axes, the graphs of the following
functions.
(a) f sxd − x
(b) tsxd − x 2
3
(c) hsxd − x
(d) jsxd − x 4
8. Draw, by hand, a rough sketch of the graph of each function.
(a) y − sin x
(b) y − tan x
(c) y − e x
(d) y − ln x
(e) y − 1yx
(f ) y − x
(g) y − sx
(h) y − tan21 x
| |
12. (a) What is a one-to-one function? How can you tell if a
function is one-to-one by looking at its graph?
(b) If f is a one-to-one function, how is its inverse function
f 21 defined? How do you obtain the graph of f 21 from
the graph of f ?
13. (a) How is the inverse sine function f sxd − sin21 x defined?
What are its domain and range?
(b) How is the inverse cosine function f sxd − cos21 x
defined? What are its domain and range?
(c) How is the inverse tangent function f sxd − tan21 x
defined? What are its domain and range?
TRUE-FALSE QUIZ
Determine whether the statement is true or false. If it is true,
explain why. If it is false, explain why or give an example that
disproves the statement.
9. If 0 , a , b, then ln a , ln b.
1. If f is a function, then f ss 1 td − f ssd 1 f std.
10. If x . 0, then sln xd6 − 6 ln x.
8. You can always divide by e x.
2. If f ssd − f std, then s − t.
3. If f is a function, then f s3xd − 3 f sxd.
11. If x . 0 and a . 1, then
4. If the function f has an inverse and f s2d − 3, then f 21s3d − 2.
12. tan21s21d − 3!y4
5. A vertical line intersects the graph of a function at most once.
6. If f and t are functions, then f 8 t − t 8 f.
7. If f is one-to-one, then f 21sxd −
1
.
f sxd
13. tan21x −
ln x
x
− ln .
ln a
a
sin21x
cos21x
14. If x is any real number, then sx 2 − x.
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68
CHAPTER 1
Functions and Models
EXERCISES
1. Let f be the function whose graph is given.
10. The graph of f is given. Draw the graphs of the following
functions.
(a) y − f sx 2 8d
(b) y − 2f sxd
(c) y − 2 2 f sxd
(d) y − 12 f sxd 2 1
21
(e) y − f sxd
(f ) y − f 21sx 1 3d
y
f
1
y
x
1
1
(a) Estimate the value of f s2d.
(b) Estimate the values of x such that f sxd − 3.
(c) State the domain of f.
(d) State the range of f.
(e) On what interval is f increasing?
(f ) Is f one-to-one? Explain.
(g) Is f even, odd, or neither even nor odd? Explain.
2. The graph of t is given.
y
g
1
0 1
x
(a) State the value of ts2d.
(b) Why is t one-to-one?
(c) Estimate the value of t21s2d.
(d) Estimate the domain of t21.
(e) Sketch the graph of t21.
3. If f sxd − x 2 2 2x 1 3, evaluate the difference quotient
f sa 1 hd 2 f sad
h
4. Sketch a rough graph of the yield of a crop as a function of
the amount of fertilizer used.
5–8 Find the domain and range of the function. Write your
answer in interval notation.
5. f sxd − 2ys3x 2 1d
6. tsxd − s16 2 x 4
7. hsxd − lnsx 1 6d
8. Fstd − 3 1 cos 2t
9. Suppose that the graph of f is given. Describe how the graphs
of the following functions can be obtained from the graph of f.
(a) y − f sxd 1 5
(b) y − f sx 1 5d
(c) y − 1 1 2 f sxd
(d) y − f sx 2 2d 2 2
(e) y − 2f sxd
(f ) y − f 21sxd
0
1
x
11–18 Use transformations to sketch the graph of the function.
11. f sxd − x 3 1 2
12. f sxd − sx 2 3d2
13. y − sx 1 2
14. y − lnsx 1 5d
15. tsxd − 1 1 cos 2x
16. hsxd − 2e x 1 2
17. ssxd − 1 1 0.5 x
2x
18. f sxd − b x
e 21
if x , 0
if x > 0
19. Determine whether f is even, odd, or neither even nor odd.
(a) f sxd − 2x 5 2 3x 2 1 2
(b) f sxd − x 3 2 x 7
2
(c) f sxd − e2x
(d) f sxd − 1 1 sin x
(e) f sxd − 1 2 cos 2x
(f ) f sxd − sx 1 1d2
20. Find an expression for the function whose graph consists of
the line segment from the point s22, 2d to the point s21, 0d
together with the top half of the circle with center the origin
and radius 1.
21. If f sxd − ln x and tsxd − x 2 2 9, find the functions
(a) f 8 t, (b) t 8 f , (c) f 8 f , (d) t 8 t, and their domains.
22. Express the function Fsxd − 1ysx 1 sx as a composition of
three functions.
23. Life expectancy has improved dramatically in recent decades.
The table gives the life expectancy at birth (in years) of males
born in the United States. Use a scatter plot to choose an
appropriate type of model. Use your model to predict the life
span of a male born in the year 2030.
Birth year Life expectancy
1900
1910
1920
1930
1940
1950
48.3
51.1
55.2
57.4
62.5
65.6
Birth year Life expectancy
1960
1970
1980
1990
2000
2010
66.6
67.1
70.0
71.8
73.0
76.2
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CHAPTER 1
24. A small-appliance manufacturer finds that it costs $9000 to
produce 1000 toaster ovens a week and $12,000 to produce
1500 toaster ovens a week.
(a) Express the cost as a function of the number of toaster
ovens produced, assuming that it is linear. Then sketch
the graph.
(b) What is the slope of the graph and what does it
represent?
(c) What is the y-intercept of the graph and what does it
represent?
25. If f sxd − 2x 1 4 , find f
x
31. e 2x − 3
x
35. tan21s3x 2d −
27. Use the laws of logarithms to expand each expression.
Î
x2 1 1
x21
29–30 Find the exact value of each expression.
30. (a) ln
1
e3
36. ln x 2 1 − lns5 1 xd 2 4
Pstd −
(b) lnsx 2 3d 1 lnsx 1 3d 2 2 lnsx 2 2 9d
29. (a) e
!
4
38. The population of a certain species in a limited environment
with initial population 100 and carrying capacity 1000 is
28. Express as a single logarithm.
(a) 12 ln x 2 2 lnsx 2 1 1d
2 ln 5
34. cos21 x − 2
37. The viral load for an HIV patient is 52.0 RNA copiesymL
before treatment begins. Eight days later the viral load is half
of the initial amount.
(a) Find the viral load after 24 days.
(b) Find the viral load Vstd that remains after t days.
(c) Find a formula for the inverse of the function V and
explain its meaning.
(d) After how many days will the viral load be reduced to
2.0 RNA copiesymL?
2x 1 3
.
1 2 5x
(b) log 2
32. ln x 2 − 5
33. e e − 10
s6d.
(a) ln x sx 1 1
(
tan arcsin 45
(b) log 6 4 1 log 6 54
(c)
(b) sinstan21 1d
(c) 1023 log 4
69
31–36 Solve the equation for x. Give both an exact value and a
decimal approximation, correct to three decimal places.
21
26. Find the inverse function of f sxd −
Review
)
;
100,000
100 1 900e2t
where t is measured in years.
(a) Graph this function and estimate how long it takes for the
population to reach 900.
(b) Find the inverse of this function and explain its meaning.
(c) Use the inverse function to find the time required for the
population to reach 900. Compare with the result of part (a).
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Principles of Problem Solving
There are no hard and fast rules that will ensure success in solving problems. However,
it is possible to outline some general steps in the problem-solving process and to give
some principles that may be useful in the solution of certain problems. These steps and
principles are just common sense made explicit. They have been adapted from George
Polya’s book How To Solve It.
1 UNDERSTAND THE PROBLEM
The first step is to read the problem and make sure that you understand it clearly. Ask
yourself the following questions:
What is the unknown?
What are the given quantities?
What are the given conditions?
For many problems it is useful to
draw a diagram
and identify the given and required quantities on the diagram.
Usually it is necessary to
introduce suitable notation
In choosing symbols for the unknown quantities we often use letters such as a, b, c, m, n,
x, and y, but in some cases it helps to use initials as suggestive symbols; for instance, V
for volume or t for time.
2 THINK OF A PLAN
Find a connection between the given information and the unknown that will enable you
to calculate the unknown. It often helps to ask yourself explicitly: “How can I relate the
given to the unknown?” If you don’t see a connection immediately, the following ideas
may be helpful in devising a plan.
Try to Recognize Something Familiar Relate the given situation to previous knowledge.
Look at the unknown and try to recall a more familiar problem that has a similar unknown.
Try to Recognize Patterns Some problems are solved by recognizing that some kind of
pattern is occurring. The pattern could be geometric, or numerical, or algebraic. If you can
see regularity or repetition in a problem, you might be able to guess what the continuing
pattern is and then prove it.
Use Analogy Try to think of an analogous problem — that is, a similar problem, a related
problem — but one that is easier than the original problem. If you can solve the similar,
simpler problem, then it might give you the clues you need to solve the original, more
difficult problem. For instance, if a problem involves very large numbers, you could first
try a similar problem with smaller numbers. Or if the problem involves three-dimensional
geometry, you could look for a similar problem in two-dimensional geometry. Or if the
problem you start with is a general one, you could first try a special case.
Introduce Something Extra It may sometimes be necessary to introduce something
new — an auxiliary aid — to help make the connection between the given and the unknown.
For instance, in a problem where a diagram is useful the auxiliary aid could be a new line
drawn in a diagram. In a more algebraic problem it could be a new unknown that is
related to the original unknown.
Take Cases We may sometimes have to split a problem into several cases and give a
different argument for each of the cases. For instance, we often have to use this strategy
in dealing with absolute value.
70
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Work Backward Sometimes it is useful to imagine that your problem is solved and then
to work backward, step by step, until you arrive at the given data. At this point you may
be able to reverse your steps and thereby construct a solution to the original problem.
This procedure is commonly used in solving equations. For instance, in solving the equation 3x 2 5 − 7, we suppose that x is a number that satisfies 3x 2 5 − 7 and work
backward. We add 5 to each side of the equation and then divide each side by 3 to get
x − 4. Since each of these steps can be reversed, we have solved the problem.
Establish Subgoals In a complex problem it is often useful to set subgoals (in which the
desired situation is only partially fulfilled). If we can first reach these subgoals, then we
may be able to build on them to reach our final goal.
Indirect Reasoning Sometimes it is appropriate to attack a problem indirectly. In using
proof by contradiction to prove that P implies Q, we assume that P is true and Q is false
and try to see why this can’t happen. Somehow we have to use this information and arrive
at a contradiction to what we absolutely know is true.
Mathematical Induction In proving statements that involve a positive integer n, it is
frequently helpful to use the following principle.
Principle of Mathematical Induction Let Sn be a statement about the positive
integer n. Suppose that
1. S1 is true.
2. Sk11 is true whenever Sk is true.
Then Sn is true for all positive integers n.
This is reasonable because, since S1 is true, it follows from condition 2 swith k − 1d
that S2 is true. Then, using condition 2 with k − 2, we see that S3 is true. Again using
condition 2, this time with k − 3, we have that S4 is true. This procedure can be followed
indefinitely.
3 CARRY OUT THE PLAN
In Step 2 a plan was devised. In carrying out that plan we have to check each stage of the
plan and write the details that prove that each stage is correct.
4 LOOK BACK
Having completed our solution, it is wise to look back over it, partly to see if we have
made errors in the solution and partly to see if we can think of an easier way to solve the
problem. Another reason for looking back is that it will familiarize us with the method of
solution and this may be useful for solving a future problem. Descartes said, “Every
problem that I solved became a rule which served afterwards to solve other problems.”
These principles of problem solving are illustrated in the following examples. Before
you look at the solutions, try to solve these problems yourself, referring to these principles of problem solving if you get stuck. You may find it useful to refer to this section
from time to time as you solve the exercises in the remaining chapters of this book.
EXAMPLE 1 Express the hypotenuse h of a right triangle with area 25 m2 as a function
of its perimeter P.
PS Understand the problem.
SOLUTION Let’s first sort out the information by identifying the unknown quantity and
the data:
Unknown: hypotenuse h
Given quantities: perimeter P, area 25 m 2
71
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PS Draw a diagram.
It helps to draw a diagram and we do so in Figure 1.
h
FIGURE 1
PS Connect the given with the unknown.
PS Introduce something extra.
b
a
In order to connect the given quantities to the unknown, we introduce two extra
variables a and b, which are the lengths of the other two sides of the triangle. This
enables us to express the given condition, which is that the triangle is right-angled, by
the Pythagorean Theorem:
h2 − a2 1 b2
The other connections among the variables come by writing expressions for the area
and perimeter:
25 − 12 ab
P−a1b1h
Since P is given, notice that we now have three equations in the three unknowns a, b,
and h:
PS Relate to the familiar.
1
h2 − a2 1 b2
2
25 − 12 ab
3
P−a1b1h
Although we have the correct number of equations, they are not easy to solve in a
straightforward fashion. But if we use the problem-solving strategy of trying to
recognize something familiar, then we can solve these equations by an easier method.
Look at the right sides of Equations 1, 2, and 3. Do these expressions remind you of
anything familiar? Notice that they contain the ingredients of a familiar formula:
sa 1 bd2 − a 2 1 2ab 1 b 2
Using this idea, we express sa 1 bd2 in two ways. From Equations 1 and 2 we have
sa 1 bd2 − sa 2 1 b 2 d 1 2ab − h 2 1 4s25d − h 2 1 100
From Equation 3 we have
sa 1 bd2 − sP 2 hd2 − P 2 2 2Ph 1 h 2
Thus
h 2 1 100 − P 2 2 2Ph 1 h 2
2Ph − P 2 2 100
h−
P 2 2 100
2P
This is the required expression for h as a function of P.
n
As the next example illustrates, it is often necessary to use the problem-solving principle of taking cases when dealing with absolute values.
72
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EXAMPLE 2 Solve the inequality | x 2 3 | 1 | x 1 2 | , 11.
SOLUTION Recall the definition of absolute value:
H
x
if x > 0
| x | − 2x if x , 0
H
H
| H
H
It follows that
x23
if x 2 3 > 0
x23
2x 1 3
if x > 3
if x , 3
x12
if x 1 2 > 0
x12
2x 2 2
if x > 22
if x , 22
| x 2 3 | − 2sx 2 3d if x 2 3 , 0
−
Similarly
| x 1 2 − 2sx 1 2d if x 1 2 , 0
−
PS Take cases.
These expressions show that we must consider three cases:
x , 22
22 < x , 3
x>3
CASE I If x , 22, we have
| x 2 3 | 1 | x 1 2 | , 11
2x 1 3 2 x 2 2 , 11
22x , 10
x . 25
CASE II If 22 < x , 3, the given inequality becomes
2x 1 3 1 x 1 2 , 11
5 , 11
(always true)
CASE III If x > 3, the inequality becomes
x 2 3 1 x 1 2 , 11
2x , 12
x,6
Combining cases I, II, and III, we see that the inequality is satisfied when 25 , x , 6.
So the solution is the interval s25, 6d.
n
In the following example we first guess the answer by looking at special cases and
recognizing a pattern. Then we prove our conjecture by mathematical induction.
In using the Principle of Mathematical Induction, we follow three steps:
Step 1 Prove that Sn is true when n − 1.
Step 2 Assume that Sn is true when n − k and deduce that Sn is true when n − k 1 1.
Step 3 Conclude that Sn is true for all n by the Principle of Mathematical Induction.
73
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EXAMPLE 3 If f0sxd − xysx 1 1d and fn11 − f0 8 fn for n − 0, 1, 2, . . . , find a formula
for fnsxd.
PS Analogy: Try a similar, simpler
problem.
SOLUTION We start by finding formulas for fnsxd for the special cases n − 1, 2, and 3.
f1sxd − s f0 8 f0dsxd − f0( f0sxd) − f0
S D
x
x11
x
x
x11
x11
x
−
−
−
x
2x 1 1
2x 1 1
11
x11
x11
f2sxd − s f0 8 f1 dsxd − f0( f1sxd) − f0
S
x
2x 1 1
D
x
x
2x 1 1
2x 1 1
x
−
−
−
x
3x 1 1
3x 1 1
11
2x 1 1
2x 1 1
f3sxd − s f0 8 f2 dsxd − f0( f2sxd) − f0
S
x
3x 1 1
D
x
x
3x 1 1
3x 1 1
x
−
−
−
x
4x 1 1
4x 1 1
11
3x 1 1
3x 1 1
PS Look for a pattern.
We notice a pattern: the coefficient of x in the denominator of fnsxd is n 1 1 in the
three cases we have computed. So we make the guess that, in general,
4
fnsxd −
x
sn 1 1dx 1 1
To prove this, we use the Principle of Mathematical Induction. We have already verified
that (4) is true for n − 1. Assume that it is true for n − k, that is,
fksxd −
Then
x
sk 1 1dx 1 1
fk11sxd − s f0 8 fk dsxd − f0( fksxd) − f0
S
x
sk 1 1dx 1 1
D
x
x
sk 1 1d x 1 1
sk 1 1d x 1 1
x
−
−
−
x
sk 1 2dx 1 1
sk 1 2d x 1 1
11
sk 1 1dx 1 1
sk 1 1dx 1 1
This expression shows that (4) is true for n − k 1 1. Therefore, by mathematical
induction, it is true for all positive integers n.
n
74
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Problems
1. One of the legs of a right triangle has length 4 cm. Express the length of the altitude
perpendicular to the hypotenuse as a function of the length of the hypotenuse.
2. The altitude perpendicular to the hypotenuse of a right triangle is 12 cm. Express the length
of the hypotenuse as a function of the perimeter.
|
|| − 3.
4. Solve the inequality | x 2 1 | 2 | x 2 3 | > 5.
|
3. Solve the equation 4x 2 x 1 1
|
| | |
6. Sketch the graph of the function tsxd − | x 2 1 | 2 | x 2 4 |.
7. Draw the graph of the equation x 1 | x | − y 1 | y |.
5. Sketch the graph of the function f sxd − x 2 2 4 x 1 3 .
2
2
8. Sketch the region in the plane consisting of all points sx, yd such that
|x 2 y| 1 |x| 2 |y| < 2
9. The notation maxha, b, . . .j means the largest of the numbers a, b, . . . . Sketch the graph of
each function.
(a) f sxd − maxhx, 1yxj
(b) f sxd − maxhsin x, cos xj
(c) f sxd − maxhx 2, 2 1 x, 2 2 xj
10. Sketch the region in the plane defined by each of the following equations or inequalities.
(a) maxhx, 2yj − 1
(b) 21 < maxhx, 2yj < 1
(c) maxhx, y 2 j − 1
11. Show that if x . 0 and x Þ 1, then
1
1
1
1
1
1
−
log 2 x
log 3 x
log 5 x
log 30 x
12. Find the number of solutions of the equation sin x −
x
.
100
13. Find the exact value of
sin
!
2!
3!
200!
1 sin
1 sin
1 ∙ ∙ ∙ 1 sin
100
100
100
100
14. (a) Show that the function f sxd − ln ( x 1 sx 2 1 1 ) is an odd function.
(b) Find the inverse function of f.
15. Solve the inequality lnsx 2 2 2x 2 2d < 0.
16. Use indirect reasoning to prove that log 2 5 is an irrational number.
17. A driver sets out on a journey. For the first half of the distance she drives at the leisurely
pace of 30 miyh; she drives the second half at 60 miyh. What is her average speed on
this trip?
75
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18. Is it true that f 8 s t 1 hd − f 8 t 1 f 8 h ?
19. Prove that if n is a positive integer, then 7 n 2 1 is divisible by 6.
20. Prove that 1 1 3 1 5 1 ∙ ∙ ∙ 1 s2n 2 1d − n 2.
21. If f0sxd − x 2 and fn11sxd − f0s fnsxdd for n − 0, 1, 2, . . . , find a formula for fnsxd.
1
and fn11 − f0 8 fn for n − 0, 1, 2, . . . , find an expression for fnsxd and
22x
use mathematical induction to prove it.
22. (a) If f0sxd −
;
(b) Graph f0 , f1, f2 , f3 on the same screen and describe the effects of repeated composition.
76
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We know that when an object is dropped from a height it falls faster and faster. Galileo discovered that the distance the object has
fallen is proportional to the square of the time elapsed. Calculus enables us to calculate the precise speed of the object at any time.
In Exercise 2.7.11 you are asked to determine the speed at which a cliff diver plunges into the ocean.
Icealex / Shutterstock.com
2
Limits and Derivatives
IN A PREVIEW OF CALCULUS (immediately preceding Chapter 1) we saw how the idea of a limit
underlies the various branches of calculus. It is therefore appropriate to begin our study of calculus
by investigating limits and their properties. The special type of limit that is used to find tangents
and velocities gives rise to the central idea in differential calculus, the derivative.
77
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78
CHAPTER 2
Limits and Derivatives
2.1 The Tangent and Velocity Problems
In this section we see how limits arise when we attempt to find the tangent to a curve or
the velocity of an object.
L
■ The Tangent Problem
(a)
P
C
L
The word tangent is derived from the Latin word tangens, which means “touching.” We
can think of a tangent to a curve as a line that touches the curve and follows the same
direction as the curve at the point of contact. How can this idea be made precise?
For a circle we could simply follow Euclid and say that a tangent is a line ! that intersects the circle once and only once, as in Figure 1(a). For more complicated curves this
definition is inadequate. Figure l(b) shows a line ! that appears to be a tangent to the
curve C at point P, but it intersects C twice.
To be specific, let’s look at the problem of trying to find a tangent line ! to the parabola y − x 2 in the following example.
EXAMPLE 1 Find an equation of the tangent line to the parabola y − x 2 at the
(b)
point Ps1, 1d.
FIGURE 1
y
Q { x, ≈}
y=≈
L
P (1, 1)
x
0
SOLUTION We will be able to find an equation of the tangent line ! as soon as we
know its slope m. The difficulty is that we know only one point, P, on !, whereas
we need two points to compute the slope. But observe that we can compute an
approximation to m by choosing a nearby point Qsx, x 2 d on the parabola (as in
Figure 2) and computing the slope mPQ of the secant line PQ. (A secant line, from
the Latin word secans, meaning cutting, is a line that cuts [intersects] a curve more
than once.)
We choose x ± 1 so that Q ± P. Then
mPQ −
FIGURE 2
x2 2 1
x21
For instance, for the point Qs1.5, 2.25d we have
mPQ −
x
mPQ
2
1.5
1.1
1.01
1.001
3
2.5
2.1
2.01
2.001
x
mPQ
0
0.5
0.9
0.99
0.999
1
1.5
1.9
1.99
1.999
2.25 2 1
1.25
−
− 2.5
1.5 2 1
0.5
The tables in the margin show the values of mPQ for several values of x close to 1. The
closer Q is to P, the closer x is to 1 and, it appears from the tables, the closer mPQ is
to 2. This suggests that the slope of the tangent line ! should be m − 2.
We say that the slope of the tangent line is the limit of the slopes of the secant lines,
and we express this symbolically by writing
lim mPQ − m
Q lP
x2 2 1
−2
xl1 x 2 1
and
lim
Assuming that the slope of the tangent line is indeed 2, we use the point-slope form
of the equation of a line [ y 2 y1 − msx 2 x 1d, see Appendix B] to write the equation
of the tangent line through s1, 1d as
y 2 1 − 2sx 2 1d
or
y − 2x 2 1
n
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SECTION 2.1
The Tangent and Velocity Problems
79
Figure 3 illustrates the limiting process that occurs in Example 1. As Q approaches P
along the parabola, the corresponding secant lines rotate about P and approach the tangent line !.
y
Q
y
y
L
L
L
Q
P
P
0
x
P
x
0
Q
x
0
Q approaches P from the right
y
Q
y
L
P
Q
x
0
y
L
P
L
Q
P
x
x
0
Q approaches P from the left
FIGURE 3
Many functions that occur in the sciences are not described by explicit equations; they
are defined by experimental data. The next example shows how to estimate the slope of
the tangent line to the graph of such a function.
t
Q
0
0.02
0.04
0.06
0.08
0.1
10
8.187
6.703
5.488
4.493
3.676
EXAMPLE 2 A pulse laser operates by storing charge on a capacitor and releasing it
suddenly when the laser is fired. The data in the table describe the charge Q remaining
on the capacitor (measured in coulombs) at time t (measured in seconds after the laser
is fired). Use the data to draw the graph of this function and estimate the slope of the
tangent line at the point where t − 0.04. (Note: The slope of the tangent line represents
the electric current flowing from the capacitor to the laser [measured in amperes].)
SOLUTION In Figure 4 we plot the given data and use these points to sketch a curve
that approximates the graph of the function.
Q (coulombs)
10
8
6
4
FIGURE 4
0
0.02
0.04
0.06
0.08
0.1
t (seconds)
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80
CHAPTER 2
Limits and Derivatives
Given the points Ps0.04, 6.703d and Rs0, 10d on the graph, we find that the slope of
the secant line PR is
mPR −
R
mPR
(0, 10)
(0.02, 8.187)
(0.06, 5.488)
(0.08, 4.493)
(0.1, 3.676)
282.425
274.200
260.750
255.250
250.450
10 2 6.703
− 282.425
0 2 0.04
The table at the left shows the results of similar calculations for the slopes of other
secant lines. From this table we would expect the slope of the tangent line at t − 0.04
to lie somewhere between 274.20 and 260.75. In fact, the average of the slopes of the
two closest secant lines is
1
2 s274.20 2 60.75d − 267.475
So, by this method, we estimate the slope of the tangent line to be about 267.5.
Another method is to draw an approximation to the tangent line at P and measure
the sides of the triangle ABC, as in Figure 5.
Q (coulombs)
10
9
8
A
P
7
6
FIGURE 5
The physical meaning of the answer
in Example 2 is that the electric
current flowing from the capacitor to
the laser after 0.04 seconds is about
!65 amperes.
5
B
0
0.02
C
0.04
0.06
0.08
0.1
t (seconds)
This gives an estimate of the slope of the tangent line as
2
| AB | < 2 8.0 2 5.4 − 265.0
0.06 2 0.02
| BC |
n
■ The Velocity Problem
If you watch the speedometer of a car as you drive in city traffic, you see that the speed
doesn’t stay the same for very long; that is, the velocity of the car is not constant. We
assume from watching the speedometer that the car has a definite velocity at each
moment, but how is the “instantaneous” velocity defined?
Let’s consider the velocity problem: Find the instantaneous velocity of an object moving along a straight path at a specific time if the position of the object at any time is
known. In the next example, we investigate the velocity of a falling ball. Through experiments carried out four centuries ago, Galileo discovered that the distance fallen by any
freely falling body is proportional to the square of the time it has been falling. (This
model for free fall neglects air resistance.) If the distance fallen after t seconds is denoted
by sstd and measured in meters, then (at the earth’s surface) Galileo’s observation is
expressed by the equation
sstd − 4.9t 2
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SECTION 2.1
The Tangent and Velocity Problems
81
EXAMPLE 3 Suppose that a ball is dropped from the upper observation deck of
the CN Tower in Toronto, 450 m above the ground. Find the velocity of the ball after
5 seconds.
SOLUTION The difficulty in finding the instantaneous velocity at 5 seconds is that
we are dealing with a single instant of time st − 5d, so no time interval is involved.
However, we can approximate the desired quantity by computing the average velocity
over the brief time interval of a tenth of a second from t − 5 to t − 5.1:
Steve Allen / Stockbyte / Getty Images
average velocity −
s
s=4.9t @
Q
P
5+h
ss5.1d 2 ss5d
0.1
−
4.9s5.1d2 2 4.9s5d2
− 49.49 mys
0.1
Time interval
Average velocity smysd
5 < t < 5.1
49.49
5 < t < 5.05
49.245
5 < t < 5.01
5 < t < 5.001
49.049
49.0049
It appears that as we shorten the time period, the average velocity is becoming closer to
49 mys. The instantaneous velocity when t − 5 is defined to be the limiting value of
these average velocities over shorter and shorter time periods that start at t − 5. Thus it
appears that the (instantaneous) velocity after 5 seconds is 49 mys.
n
slope of secant line
! average velocity
5
−
The following table shows the results of similar calculations of the average velocity
over successively smaller time periods.
CN Tower in Toronto
0
t
s
s=4.9t @
You may have the feeling that the calculations used in solving this problem are very
similar to those used earlier in this section to find tangents. In fact, there is a close connection between the tangent problem and the velocity problem. If we draw the graph of
the distance function of the ball (as in Figure 6) and we consider the points Ps5, 4.9s5d 2 d
and Qs5 1 h, 4.9s5 1 hd2 d on the graph, then the slope of the secant line PQ is
mPQ −
slope of tangent line
! instantaneous velocity
P
0
5
FIGURE 6
change in position
time elapsed
t
4.9s5 1 hd2 2 4.9s5d 2
s5 1 hd 2 5
which is the same as the average velocity over the time interval f5, 5 1 hg. Therefore the
velocity at time t − 5 (the limit of these average velocities as h approaches 0) must be
equal to the slope of the tangent line at P (the limit of the slopes of the secant lines).
Examples 1 and 3 show that in order to solve tangent and velocity problems we must
be able to find limits. After studying methods for computing limits in the next five sections, we will return to the problems of finding tangents and velocities in Section 2.7.
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82
CHAPTER 2
2.1
Limits and Derivatives
Exercises
1. A tank holds 1000 gallons of water, which drains from the
bottom of the tank in half an hour. The values in the table
show the volume V of water remaining in the tank (in gallons)
after t minutes.
t smind
5
10
15
20
25
30
V sgald
694
444
250
111
28
0
(a) If P is the point s15, 250d on the graph of V, find the
slopes of the secant lines PQ when Q is the point on the
graph with t − 5, 10, 20, 25, and 30.
(b) Estimate the slope of the tangent line at P by averaging
the slopes of two secant lines.
(c) Use a graph of V to estimate the slope of the tangent line
at P. (This slope represents the rate at which the water is
flowing from the tank after 15 minutes.)
2. A student bought a smartwatch that tracks the number of
steps she walks throughout the day. The table shows the number of steps recorded t minutes after 3:00 pm on the first day
she wore the watch.
t smind
0
10
20
30
40
Steps
3438
4559
5622
6536
7398
(a) Find the slopes of the secant lines corresponding to the
given intervals of t. What do these slopes represent?
(i) [0, 40]
(ii) [10, 20]
(iii) [20, 30]
(b) Estimate the student’s walking pace, in steps per minute,
at 3:20 pm by averaging the slopes of two secant lines.
3. The point Ps2, 21d lies on the curve y − 1ys1 2 xd.
(a) If Q is the point sx, 1ys1 2 xdd, find the slope of the
secant line PQ (correct to six decimal places) for the
following values of x :
(i) 1.5
(ii) 1.9
(iii) 1.99
(iv) 1.999
(v) 2.5
(vi) 2.1
(vii) 2.01
(viii) 2.001
(b) Using the results of part (a), guess the value of the slope
of the tangent line to the curve at Ps2, 21d.
(c) Using the slope from part (b), find an equation of the
tangent line to the curve at Ps2, 21d.
4. The point Ps0.5, 0d lies on the curve y − cos !x .
(a) If Q is the point s x, cos !xd, find the slope of the secant
line PQ (correct to six decimal places) for the following
values of x :
(i) 0
(ii) 0.4
(iii) 0.49
(iv) 0.499
(v) 1
(vi) 0.6
(vii) 0.51
(viii) 0.501
(b) Using the results of part (a), guess the value of the slope
of the tangent line to the curve at Ps0.5, 0d.
(c) Using the slope from part (b), find an equation of the
tangent line to the curve at Ps0.5, 0d.
(d) Sketch the curve, two of the secant lines, and the tangent
line.
5. The deck of a bridge is suspended 275 feet above a river. If a
pebble falls off the side of the bridge, the height, in feet, of
the pebble above the water surface after t seconds is given
by y − 275 2 16t 2.
(a) Find the average velocity of the pebble for the time
period beginning when t − 4 and lasting
(i) 0.1 seconds (ii) 0.05 seconds (iii) 0.01 seconds
(b) Estimate the instantaneous velocity of the pebble after
4 seconds.
6. If a rock is thrown upward on the planet Mars with a velocity
of 10 mys, its height in meters t seconds later is given by
y − 10 t 2 1.86t 2.
(a) Find the average velocity over the given time intervals:
(i) [1, 2]
(ii) [1, 1.5]
(iii) [1, 1.1]
(iv) [1, 1.01]
(v) [1, 1.001]
(b) Estimate the instantaneous velocity when t − 1.
7. The table shows the position of a motorcyclist after accelerating from rest.
t ssecondsd
0
1
s (feet)
0
4.9 20.6 46.5 79.2 124.8 176.7
2
3
4
5
6
(a) Find the average velocity for each time period:
(i) f2, 4g
(ii) f3, 4g
(iii) f4, 5g
(iv) f4, 6g
(b) Use the graph of s as a function of t to estimate the
instantaneous velocity when t − 3.
8. The displacement (in centimeters) of a particle moving back
and forth along a straight line is given by the equation of
motion s − 2 sin !t 1 3 cos !t, where t is measured in
seconds.
(a) Find the average velocity during each time period:
(i) f1, 2g
(ii) f1, 1.1g
(iii) f1, 1.01g
(iv) f1, 1.001g
(b) Estimate the instantaneous velocity of the particle
when t − 1.
9. The point Ps1, 0d lies on the curve y − sins10!yxd.
(a) If Q is the point sx, sins10!yxdd, find the slope of the
secant line PQ (correct to four decimal places) for x − 2,
1.5, 1.4, 1.3, 1.2, 1.1, 0.5, 0.6, 0.7, 0.8, and 0.9. Do the
slopes appear to be approaching a limit?
;
(b) Use a graph of the curve to explain why the slopes of the
secant lines in part (a) are not close to the slope of the
tangent line at P.
(c) By choosing appropriate secant lines, estimate the slope
of the tangent line at P.
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SECTION 2.2
The Limit of a Function
83
2.2 The Limit of a Function
Having seen in the preceding section how limits arise when we want to find the tangent
to a curve or the velocity of an object, we now turn our attention to limits in general and
numerical and graphical methods for computing them.
■ Finding Limits Numerically and Graphically
Let’s investigate the behavior of the function f defined by f sxd − sx 2 1dysx 2 2 1d for
values of x near 1. The following table gives values of f sxd for values of x close to 1 but
not equal to 1.
x,1
f sxd
x.1
f sxd
0.5
0.9
0.99
0.999
0.9999
0.666667
0.526316
0.502513
0.500250
0.500025
1.5
1.1
1.01
1.001
1.0001
0.400000
0.476190
0.497512
0.499750
0.499975
1
0.5
1
0.5
y
y=
ƒ
approaches 0.5
0.5
0
x-1
≈-1
1
x
From the table and the graph of f shown in Figure 1 we see that the closer x is to 1
(on either side of 1), the closer f sxd is to 0.5. In fact, it appears that we can make the
values of f sxd as close as we like to 0.5 by taking x sufficiently close to 1. We express
this by saying “the limit of the function f sxd − sx 2 1dysx 2 2 1d as x approaches 1 is
equal to 0.5.” The notation for this is
as x approaches 1
x21
− 0.5
x l1 x 2 2 1
lim
FIGURE 1
In general, we use the following notation.
1 Intuitive Definition of a Limit Suppose f sxd is defined when x is near the
number a. (This means that f is defined on some open interval that contains a,
except possibly at a itself.) Then we write
lim f sxd − L
xla
and say
“the limit of f sxd, as x approaches a, equals L”
if we can make the values of f sxd arbitrarily close to L (as close to L as we like)
by restricting x to be sufficiently close to a (on either side of a) but not equal to a.
Roughly speaking, this says that the values of f sxd approach L as x approaches a. In
other words, the values of f sxd tend to get closer and closer to the number L as x gets
closer and closer to the number a (from either side of a) but x ± a. (A more precise
definition will be given in Section 2.4.)
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84
CHAPTER 2
Limits and Derivatives
An alternative notation for
lim f sxd − L
xla
f sxd l L
is
as
xla
which is usually read “ f sxd approaches L as x approaches a.”
Notice the phrase “but x not equal to a” in the definition of limit. This means that in
finding the limit of f sxd as x approaches a, we never consider x − a. In fact, f sxd need
not even be defined when x − a. The only thing that matters is how f is defined near a.
Figure 2 shows the graphs of three functions. Note that in part (b), f sad is not defined
and in part (c), f sad ± L. But in each case, regardless of what happens at a, it is true
that lim x l a f sxd − L.
y
y
y
L
L
L
0
a
0
x
(a)
a
0
x
a
x
(c)
(b)
FIGURE 2 lim f sxd − L in all three cases
xla
st 2 1 9 2 3
.
tl0
t2
EXAMPLE 1 Estimate the value of lim
SOLUTION The table lists values of the function for several values of t near 0.
t
st 2 1 9 2 3
t2
60.001
60.0001
60.00001
60.000001
0.166667
0.166670
0.167000
0.000000
t
st 2 1 9 2 3
t2
61.0
0.162277 . . .
60.5
0.165525 . . .
60.1
0.166620 . . .
60.05
0.166655 . . .
60.01
0.166666 . . .
As t approaches 0, the values of the function seem to approach 0.1666666 . . . and so
we guess that
1
st 2 1 9 2 3
lim
−
n
2
tl0
t
6
In Example 1 what would have happened if we had taken even smaller values of t? The
table in the margin shows the results from one calculator; you can see that something
strange seems to be happening.
If you try these calculations on your own calculator you might get different values,
but eventually you will get the value 0 if you make t sufficiently small. Does this
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SECTION 2.2
www.StewartCalculus.com
For a further explanation of why
calculators sometimes give false
values, click on Lies My Calculator
and Computer Told Me. In particular, see the section called The Perils
of Subtraction.
The Limit of a Function
85
mean that the answer is really 0 instead of 16 ? No, the value of the limit is 16 , as we will
show in the next section. The problem is that the calculator gave false values because
st 2 1 9 is very close to 3 when t is small. (In fact, when t is sufficiently small, a
calculator’s value for st 2 1 9 is 3.000 . . . to as many digits as the calculator is
capable of carrying.)
Something similar happens when we try to graph the function
f std −
st 2 1 9 2 3
t2
of Example 1 on a graphing calculator or computer. Parts (a) and (b) of Figure 3
show quite accurate graphs of f , and if we trace along the curve, we can estimate
easily that the limit is about 16 . But if we zoom in too much, as in parts (c) and (d), then
we get inaccurate graphs, again due to rounding errors within the calculations.
0.2
0.2
0.1
0.1
(a) _5¯t¯5
(b) _0.1¯t¯0.1
(c) _10 _6¯t¯10 _6
(d) _10 _7¯t¯10 _7
FIGURE 3
EXAMPLE 2 Guess the value of lim
xl0
x
sin x
x
61.0
60.5
60.4
60.3
60.2
60.1
60.05
60.01
60.005
60.001
0.84147098
0.95885108
0.97354586
0.98506736
0.99334665
0.99833417
0.99958339
0.99998333
0.99999583
0.99999983
sin x
.
x
SOLUTION The function f sxd − ssin xdyx is not defined when x − 0. Using a calculator (and remembering that, if x [ R, sin x means the sine of the angle whose radian
measure is x), we construct a table of values correct to eight decimal places. From the
table at the left and the graph in Figure 4 we guess that
lim
xl0
sin x
−1
x
This guess is in fact correct, as will be proved in Chapter 3 using a geometric
argument.
y
FIGURE 4
_1
1
y=
0
1
sin x
x
x
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n
86
CHAPTER 2
Limits and Derivatives
S
EXAMPLE 3 Find lim x 3 1
xl0
D
cos 5x
.
10,000
SOLUTION As before, we construct a table of values. From the first table it appears that
the limit might be zero.
x3 1
x
1
0.5
0.1
0.05
0.01
cos 5x
10,000
x
1.000028
0.124920
0.001088
0.000222
0.000101
0.005
0.001
x3 1
cos 5x
10,000
0.00010009
0.00010000
But if we persevere with smaller values of x, the second table suggests that the limit is
more likely to be 0.0001. In Section 2.5 we will be able to show that lim x l 0 cos 5x − 1
and that it follows that
cos 5x
1
lim x 3 1
−
− 0.0001
n
xl0
10,000
10,000
S
D
■ One-Sided Limits
y
The Heaviside function H is defined by
1
0
FIGURE 5
The Heaviside function
Hstd −
t
H
0 if t , 0
1 if t > 0
(This function is named after the electrical engineer Oliver Heaviside [1850 –1925] and
can be used to describe an electric current that is switched on at time t − 0.) Its graph is
shown in Figure 5.
There is no single number that Hstd approaches as t approaches 0, so lim t l 0 Hstd does
not exist. However, as t approaches 0 from the left, Hstd approaches 0. As t approaches 0
from the right, Hstd approaches 1. We indicate this situation symbolically by writing
lim Hstd − 0
and
t l 02
lim Hstd − 1
t l 01
and we call these one-sided limits. The notation t l 0 2 indicates that we consider only
values of t that are less than 0. Likewise, t l 0 1 indicates that we consider only values
of t that are greater than 0.
2 Intuitive Definition of One-Sided Limits We write
lim f sxd − L
x la2
and say that the left-hand limit of f sxd as x approaches a [or the limit of f sxd as x
approaches a from the left] is equal to L if we can make the values of f sxd arbitrarily close to L by restricting x to be sufficiently close to a with x less than a.
We write
lim1 f sxd − L
x la
and say that the right-hand limit of f sxd as x approaches a [or the limit of f sxd as x
approaches a from the right] is equal to L if we can make the values of f sxd arbitrarily
close to L by restricting x to be sufficiently close to a with x greater than a.
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SECTION 2.2
87
The Limit of a Function
For instance, the notation x l 52 means that we consider only x , 5, and x l 51
means that we consider only x . 5. Definition 2 is illustrated in Figure 6.
y
y
L
ƒ
x
0
FIGURE 6
ƒ
L
x
a
a
0
x
x
(b) lim ƒ=L
(a) lim ƒ=L
x a+
x a_
Notice that Definition 2 differs from Definition 1 only in that we require x to be less
than (or greater than) a. By comparing these definitions, we see that the following is true.
3
lim f sxd − L
if and only if
xla
lim f sxd − L
and
x l a2
lim f sxd − L
x l a1
EXAMPLE 4 The graph of a function t is shown in Figure 7.
y
4
3
y=©
1
0
FIGURE 7
1
2
3
4
5
x
Use the graph to state the values (if they exist) of the following:
(a) lim2 tsxd
(b) lim1 tsxd
(c) lim tsxd
xl2
xl2
xl2
(d) lim2 tsxd
(e) lim1 tsxd
(f ) lim tsxd
xl5
xl5
xl5
SOLUTION Looking at the graph we see that the values of tsxd approach 3 as x
approaches 2 from the left, but they approach 1 as x approaches 2 from the right.
Therefore
(a) lim2 tsxd − 3
and
(b) lim1 tsxd − 1
xl2
xl2
(c) Since the left and right limits are different, we conclude from (3) that lim x l 2 tsxd
does not exist.
The graph also shows that
(d) lim2 tsxd − 2
and
xl5
(e) lim1 tsxd − 2
xl5
(f ) This time the left and right limits are the same and so, by (3), we have
lim tsxd − 2
xl5
Despite this fact, notice that ts5d ± 2.
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n
88
CHAPTER 2
Limits and Derivatives
■ How Can a Limit Fail to Exist?
We have seen that a limit fails to exist at a number a if the left- and right-hand limits are
not equal (as in Example 4). The next two examples illustrate additional ways that a limit
can fail to exist.
EXAMPLE 5 Investigate lim sin
xl0
Limits and Technology
Some software applications, including computer algebra systems
(CAS), can compute limits. In order
to avoid the types of pitfalls demonstrated in Examples 1, 3, and 5, such
applications don’t find limits by
numerical experimentation. Instead,
they use more sophisticated techniques such as computing infinite
series. You are encouraged to use
one of these resources to compute
the limits in the examples of this
section and check your answers to
the exercises in this chapter.
!
.
x
SOLUTION Notice that the function f sxd − sins!yxd is undefined at 0. Evaluating the
function for some small values of x, we get
f s1d − sin ! − 0
f ( 12 ) − sin 2! − 0
f ( 13) − sin 3! − 0
f ( 14) − sin 4! − 0
f s0.1d − sin 10! − 0
f s0.01d − sin 100! − 0
Similarly, f s0.001d − f s0.0001d − 0. On the basis of this information we might
be tempted to guess that the limit is 0, but this time our guess is wrong. Note that
although f s1ynd − sin n! − 0 for any integer n, it is also true that f sxd − 1 for
infinitely many values of x (such as 2y5 or 2y101) that approach 0. You can see this
from the graph of f shown in Figure 8.
y
y=sin(π/x)
1
_1
1
x
_1
FIGURE 8
The dashed lines near the y-axis indicate that the values of sins!yxd oscillate
between 1 and 21 infinitely often as x approaches 0.
Since the values of f sxd do not approach a fixed number as x approaches 0,
lim sin
xl0
!
does not exist
x
n
Examples 3 and 5 illustrate some of the pitfalls in guessing the value of a limit. It is
easy to guess the wrong value if we use inappropriate values of x, but it is difficult to
know when to stop calculating values. And, as the discussion after Example 1 shows,
sometimes calculators and computers give the wrong values. In the next section, however, we will develop foolproof methods for calculating limits.
Another way a limit at a number a can fail to exist is when the function values grow
arbitrarily large (in absolute value) as x approaches a.
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SECTION 2.2
EXAMPLE 6 Find lim
xl0
89
The Limit of a Function
1
if it exists.
x2
SOLUTION As x becomes close to 0, x 2 also becomes close to 0, and 1yx 2 becomes
very large. (See the following table.) In fact, it appears from the graph of the function
f sxd − 1yx 2 shown in Figure 9 that the values of f sxd can be made arbitrarily large by
taking x close enough to 0. Thus the values of f sxd do not approach a number, so
lim x l 0 s1yx 2 d does not exist.
x
1
x2
61
60.5
60.2
60.1
60.05
60.01
60.001
1
4
25
100
400
10,000
1,000,000
y
y= 1
≈
0
x
FIGURE 9
n
■ Infinite Limits; Vertical Asymptotes
To indicate the kind of behavior exhibited in Example 6, we use the notation
lim
xl0
1
−`
x2
This does not mean that we are regarding ` as a number. Nor does it mean that the limit
exists. It simply expresses the particular way in which the limit does not exist: 1yx 2 can
be made as large as we like by taking x close enough to 0.
In general, we write symbolically
lim f sxd − `
xla
to indicate that the values of f sxd tend to become larger and larger (or “increase without
bound”) as x becomes closer and closer to a.
4 Intuitive Definition of an Infinite Limit Let f be a function defined on
both sides of a, except possibly at a itself. Then
lim f sxd − `
xla
means that the values of f sxd can be made arbitrarily large (as large as we please)
by taking x sufficiently close to a, but not equal to a.
y
y=ƒ
Another notation for lim x l a f sxd − ` is
f sxd l `
0
a
x
xla
xla
Again, the symbol ` is not a number, but the expression lim x l a f sxd − ` is often read as
“the limit of f sxd, as x approaches a, is infinity”
x=a
FIGURE 10
lim f sxd − `
as
or
“ f sxd becomes infinite as x approaches a”
or
“ f sxd increases without bound as x approaches a”
This definition is illustrated graphically in Figure 10.
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90
CHAPTER 2
Limits and Derivatives
A similar sort of limit, for functions that become large negative as x gets close to a, is
defined in Definition 5 and is illustrated in Figure 11.
When we say a number is “large
negative,” we mean that it is negative but its magnitude (absolute
value) is large.
5 Definition Let f be a function defined on both sides of a, except possibly at
a itself. Then
lim f sxd − 2`
y
x=a
xla
a
0
x
means that the values of f sxd can be made arbitrarily large negative by taking x
sufficiently close to a, but not equal to a.
y=ƒ
The symbol lim x l a f sxd − 2` can be read as “the limit of f sxd, as x approaches a, is
negative infinity” or “ f sxd decreases without bound as x approaches a.” As an example
we have
FIGURE 11
lim f sxd − 2`
S D
1
lim 2 2
x
xla
xl0
− 2`
Similar definitions can be given for the one-sided infinite limits
lim f sxd − `
lim f sxd − `
x l a2
x l a1
lim f sxd − 2`
lim f sxd − 2`
x l a2
x l a1
remembering that x l a2 means that we consider only values of x that are less than a,
and similarly x l a1 means that we consider only x . a. Illustrations of these four
cases are given in Figure 12.
y
y
a
0
(a) lim ƒ=`
x
a_
x
y
a
0
x
(b) lim ƒ=`
x
a+
y
a
0
(c) lim ƒ=_`
x
a
0
x
x
(d) lim ƒ=_`
a_
x
a+
FIGURE 12
6 Definition The vertical line x − a is called a vertical asymptote of the
curve y − f sxd if at least one of the following statements is true:
lim f sxd − `
x la
lim f sxd − 2`
x la
lim f sxd − `
x l a2
lim f sxd − 2`
x l a2
lim f sxd − `
x l a1
lim f sxd − 2`
x l a1
For instance, the y-axis is a vertical asymptote of the curve y − 1yx 2 because
lim x l 0 s1yx 2 d − `. In Figure 12 the line x − a is a vertical asymptote in each of the
four cases shown. In general, knowledge of vertical asymptotes is very useful in sketching graphs.
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SECTION 2.2
EXAMPLE 7 Does the curve y −
y
y=
The Limit of a Function
91
2x
have a vertical asymptote?
x23
SOLUTION There is a potential vertical asymptote where the denominator is 0, that
is, at x − 3, so we investigate the one-sided limits there.
If x is close to 3 but larger than 3, then the denominator x 2 3 is a small positive
number and 2x is close to 6. So the quotient 2xysx 2 3d is a large positive number.
[For instance, if x − 3.01 then 2xysx 2 3d − 6.02y0.01 − 602.] Thus, intuitively, we
see that
2x
lim
−`
x l 31 x 2 3
2x
x-3
5
Likewise, if x is close to 3 but smaller than 3, then x 2 3 is a small negative number
but 2x is still a positive number (close to 6). So 2xysx 2 3d is a numerically large
negative number. Thus
2x
lim
− 2`
x l 32 x 2 3
x
0
x=3
The graph of the curve y − 2xysx 2 3d is given in Figure 13. According to Definition 6, the line x − 3 is a vertical asymptote.
FIGURE 13
n
NOTE Neither of the limits in Examples 6 and 7 exist, but in Example 6 we can write
lim x l 0 s1yx 2 d − ` because f sxd l ` as x approaches 0 from either the left or the
right. In Example 7, f sxd l ` as x approaches 3 from the right but f sxd l 2` as x
approaches 3 from the left, so we simply say that lim x l 3 f sxd does not exist.
y
EXAMPLE 8 Find the vertical asymptotes of f sxd − tan x.
SOLUTION Because
tan x −
1
3π _π
_ 2
_
π
2
0
π
2
π
3π
2
x
there are potential vertical asymptotes where cos x − 0. In fact, since cos x l 01 as
x l s!y2d2 and cos x l 02 as x l s!y2d1, whereas sin x is positive (near 1) when x
is near !y2, we have
lim
FIGURE 14
x l s!y2d2
y − tan x
y=ln x
1
tan x − `
and
lim
x l s!y2d1
tan x − 2`
This shows that the line x − !y2 is a vertical asymptote. Similar reasoning shows
y the lines x − !y2 1 n!, where n is an integer, are all vertical asymptotes of
that
y=log
f sxd − tan x. The
graph
Figure 14 confirms this.
b x,inb>1
y
0
sin x
cos x
n
1
x
Another example of a function whose graph has a vertical asymptote is the natural
x Figure 15 we see that
0
logarithmic
1 function y − ln x. From
lim ln x − 2`
x l 01
FIGURE 15
The y-axis is (a)
a vertical asymptote of
the natural logarithmic function.
and so the line(b)x − 0 (the y-axis) is a vertical asymptote. In fact, the same is true for
y − log b x provided that b . 1. (See Figures 1.5.11 and 1.5.12.)
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92
CHAPTER 2
2.2
Limits and Derivatives
Exercises
1. Explain in your own words what is meant by the equation
( j) hs2d
(k) lim1 hsxd
( l) lim2 hsxd
x l5
lim f sxd − 5
xl2
x l5
y
Is it possible for this statement to be true and yet f s2d − 3?
Explain.
2. Explain what it means to say that
lim f sxd − 3
x l 12
lim f sxd − 7
and
x l11
In this situation is it possible that lim x l 1 f sxd exists?
Explain.
_4
_2
0
2
4
x
6
3. Explain the meaning of each of the following.
(a) lim f sxd − `
(b) lim1 f sxd − 2`
x l 23
xl4
4. Use the given graph of f to state the value of each quantity,
if it exists. If it does not exist, explain why.
(a) lim2 f sxd
(b) lim1 f sxd
(c) lim f sxd
x l2
xl2
(d) f s2d
xl2
(e) lim f sxd
(f ) f s4d
xl4
7. For the function t whose graph is shown, find a number a that
satisfies the given description.
(a) lim tsxd does not exist but tsad is defined.
xla
(b) lim tsxd exists but tsad is not defined.
xla
(c) lim2 tsxd and lim1 tsxd both exist but lim tsxd does
xla
xla
xla
not exist.
(d) lim1 tsxd − tsad but lim2 tsxd Þ tsad .
xla
y
xla
y
4
2
0
2
4
0
x
5. For the function f whose graph is given, state the value of
each quantity, if it exists. If it does not exist, explain why.
(a) lim f sxd
(b) lim2 f sxd
(c) lim1 f sxd
xl1
xl3
(d) lim f sxd
xl3
(e) f s3d
xl3
2
4
6 x
8. For the function A whose graph is shown, state the following.
(a) lim Asxd
(b) lim2 Asxd
x l23
x l2
(c) lim1 Asxd
(d) lim Asxd
x l2
x l21
(e) The equations of the vertical asymptotes
y
y
4
2
0
2
4
_3
x
6. For the function h whose graph is given, state the value of
each quantity, if it exists. If it does not exist, explain why.
(a) lim 2 hsxd
(b) lim 1 hsxd
(c) lim hsxd
x l 23
x l 23
x l 23
(d) hs23d
(e) lim2 hsxd
xl 0
(f ) lim1 hsxd
(g) lim hsxd
(h) hs0d
( i) lim hsxd
xl0
x l0
xl2
0
2
x
5
9. For the function f whose graph is shown, state the following.
(a) lim f sxd
(b) lim f sxd
(c) lim f sxd
x l27
x l23
(d) lim2 f sxd
(e) lim1 f sxd
xl6
xl0
xl6
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SECTION 2.2
(f ) The equations of the vertical asymptotes
17.
f sxd − 0,
lim
x l 212
f s21d − 2,
y
18.
lim f sxd − 2,
x l 31
_7
_3
0
6
f sxd − 1,
lim f sxd − 3,
xl2
f s2d − 1
f sxd − 3,
lim
x l 232
lim
x l 211
93
The Limit of a Function
lim
x l 231
f sxd − 2,
f s23d − 2,
lim f sxd − 21,
x l 32
f s3d − 0
x
19–22 Guess the value of the limit (if it exists) by evaluating the
function at the given numbers (correct to six decimal places).
10. A patient receives a 150-mg injection of a drug every
4 hours. The graph shows the amount f std of the drug in the
bloodstream after t hours. Find
lim f std
lim f std
and
t l 122
x 2 2 3x
,
x l3 x 2 2 9
x − 3.1, 3.05, 3.01, 3.001, 3.0001,
2.9, 2.95, 2.99, 2.999, 2.9999
19. lim
t l 121
and explain the significance of these one-sided limits.
x 2 2 3x
,
x l 23 x 2 2 9
x − 22.5, 22.9, 22.95, 22.99, 22.999, 22.9999,
23.5, 23.1, 23.05, 23.01, 23.001, 23.0001
20. lim
f(t)
e 5t 2 1
,
tl0
t
300
21. lim
s2 1 hd5 2 32
,
hl 0
h
h − 60.5, 60.1, 60.01, 60.001, 60.0001
22. lim
150
0
4
8
12
16
t
11–12 Sketch the graph of the function and use it to determine
the values of a for which lim x l a f sxd exists.
H
H
ex
if x < 0
11. f sxd − x 2 1 if 0 , x , 1
ln x
if x > 1
3
x
if x < 21
s
12. f sxd − x
if 21 , x < 2
sx 2 1d2 if x . 2
xl0
24.
25. lim
sin 3"
" l 0 tan 2"
26. lim
27. lim1 x x
28. lim1 x 2 ln x
xl0
14. f sxd −
e1yx 2 2
e1yx 1 1
29.
15–18 Sketch the graph of an example of a function f that
satisfies all of the given conditions.
15. lim2 f sxd − 3,
x l 11
lim f sxd − 0,
f s1d − 2
16. lim f sxd − 4,
lim2 f sxd − 1,
lim1 f sxd − 23,
f s0d − 6,
xl8
f s8d − 21
lim
5t 2 1
t l0
t
x l0
xl8
lim
x11
x l51 x 2 5
x2
31. lim
x l 2 sx 2 2d2
33. lim1 ln (sx 2 1)
x l1
35.
xl0
1 1 p9
p l 21 1 1 p 15
ln x 2 ln 4
xl4
x24
23. lim
29–40 Determine the infinite limit.
xl0
13. f sxd − x s1 1 x 22
23–28 Use a table of values to estimate the value of the limit.
If you have a graphing device, use it to confirm your result
graphically.
x l0
; 13–14 Use the graph of the function f to state the value of each
limit, if it exists. If it does not exist, explain why.
(a) lim2 f sxd
(b) lim1 f sxd
(c) lim f sxd
xl1
t − 60.5, 60.1, 60.01, 60.001, 60.0001
1
lim
xls!y2d1 x
sec x
30. lim2
x11
x25
32. lim2
sx
sx 2 3d 5
x l5
x l3
34. lim1 lnssin xd
xl0
36.
lim x cot x
x l! 2
2
x 2 1 2x
x l 1 x 2 2x 1 1
38. lim2
39. lim sln x 2 2 x22 d
40. lim1
37. lim
xl0
x l3
xl0
x 2 1 4x
x 2 2x 2 3
S
2
D
1
2 ln x
x
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94
CHAPTER 2
Limits and Derivatives
48. (a) Evaluate the function
41. Find the vertical asymptote of the function
f sxd −
x21
2x 1 4
hsxd −
42. (a) Find the vertical asymptotes of the function
for x − 1, 0.5, 0.1, 0.05, 0.01, and 0.005.
2
y−
;
x 11
3x 2 2x 2
xl0
(b) Confirm your answer to part (a) by graphing the
function.
1
1
and lim1 3
x l1 x 2 1
x3 2 1
(a) by evaluating f sxd − 1ysx 3 2 1d for values of x that
approach 1 from the left and from the right,
(b) by reasoning as in Example 7, and
(c) from a graph of f.
x l1
;
; 44. (a) By graphing the function
f sxd −
; 49. Use a graph to estimate the equations of all the vertical
asymptotes of the curve
cos 2x 2 cos x
x2
and zooming in toward the point where the graph
crosses the y-axis, estimate the value of lim x l 0 f sxd.
(b) Check your answer in part (a) by evaluating f sxd for
values of x that approach 0.
45. (a) Estimate the value of the limit lim x l 0 s1 1 xd1yx to five
decimal places. Does this number look familiar?
(b) Illustrate part (a) by graphing the function
;
y − s1 1 xd1yx.
|
|
; 46. (a) Graph the function f sxd − e 1 ln x 2 4 for
0 < x < 5. Do you think the graph is an accurate
representation of f ?
(b) How would you get a graph that represents f better?
x
47. (a) Evaluate the function f sxd − x 2 2 s2 xy1000d for
x − 1, 0.8, 0.6, 0.4, 0.2, 0.1, and 0.05, and guess the
value of
2x
lim x 2 2
xl0
1000
S
tan x 2 x
.
x3
(c) Evaluate hsxd for successively smaller values of x until
you finally reach a value of 0 for hsxd. Are you still
confident that your guess in part (b) is correct? Explain
why you eventually obtained 0 values. (In Section 4.4 a
method for evaluating this limit will be explained.)
(d) Graph the function h in the viewing rectangle f21, 1g
by f0, 1g. Then zoom in toward the point where the
graph crosses the y-axis to estimate the limit of hsxd as
x approaches 0. Continue to zoom in until you observe
distortions in the graph of h. Compare with the results
of part (c).
(b) Guess the value of lim
43. Determine lim2
;
tan x 2 x
x3
D
(b) Evaluate f sxd for x − 0.04, 0.02, 0.01, 0.005, 0.003,
and 0.001. Guess again.
y − tans2 sin xd
2! < x < !
Then find the exact equations of these asymptotes.
50. Consider the function f sxd − tan
1
.
x
(a) Show that f sxd − 0 for x −
1 1
1
,
,
,...
! 2! 3!
(b) Show that f sxd − 1 for x −
4 4
4
,
,
,...
! 5! 9!
(c) What can you conclude about lim1 tan
xl0
1
?
x
51. In the theory of relativity, the mass of a particle with
velocity v is
m−
m0
s1 2 v 2yc 2
where m 0 is the mass of the particle at rest and c is the
speed of light. What happens as v l c2?
2.3 Calculating Limits Using the Limit Laws
■ Properties of Limits
In Section 2.2 we used calculators and graphs to guess the values of limits, but we saw
that such methods don’t always lead to the correct answers. In this section we use the
following properties of limits, called the Limit Laws, to calculate limits.
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SECTION 2.3
Calculating Limits Using the Limit Laws
95
Limit Laws Suppose that c is a constant and the limits
lim f sxd
lim tsxd
and
xla
xla
exist. Then
1. lim f f sxd 1 tsxdg − lim f sxd 1 lim tsxd
xla
xla
xla
2. lim f f sxd 2 tsxdg − lim f sxd 2 lim tsxd
xla
xla
xla
3. lim fcf sxdg − c lim f sxd
xla
xla
4. lim f f sxd tsxdg − lim f sxd ? lim tsxd
xla
xla
lim f sxd
f sxd
xla
−
x l a tsxd
lim tsxd
5. lim
xla
xla
if lim tsxd ± 0
xla
These five laws can be stated verbally as follows:
Sum Law
Difference Law
Constant Multiple Law
1. The limit of a sum is the sum of the limits.
2. The limit of a difference is the difference of the limits.
3. The limit of a constant times a function is the constant times the limit of the
function.
Product Law
4. The limit of a product is the product of the limits.
Quotient Law
5. The limit of a quotient is the quotient of the limits (provided that the limit of
the denominator is not 0).
It is easy to believe that these properties are true. For instance, if f sxd is close to L and
tsxd is close to M, it is reasonable to conclude that f sxd 1 tsxd is close to L 1 M. This
gives us an intuitive basis for believing that Law 1 is true. In Section 2.4 we give a precise definition of a limit and use it to prove this law. The proofs of the remaining laws are
given in Appendix F.
y
EXAMPLE 1 Use the Limit Laws and the graphs of f and t in Figure 1 to evaluate the
following limits, if they exist.
f
1
0
g
(a) lim f f sxd 1 5tsxdg
1
x
x l 22
(b) lim f f sxd tsxdg
xl1
(c) lim
xl2
f sxd
tsxd
SOLUTION
(a) From the graphs of f and t we see that
lim f sxd − 1
x l 22
FIGURE 1
and
lim tsxd − 21
x l 22
Therefore we have
lim f f sxd 1 5tsxdg − lim f sxd 1 lim f5tsxdg
(by Limit Law 1)
− lim f sxd 1 5 lim tsxd
(by Limit Law 3)
x l 22
x l 22
x l 22
x l 22
x l 22
− 1 1 5s21d − 24
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96
CHAPTER 2
Limits and Derivatives
(b) We see that lim x l 1 f sxd − 2. But lim x l 1 tsxd does not exist because the left and
right limits are different:
lim tsxd − 22
lim tsxd − 21
x l 12
x l 11
So we can’t use Law 4 for the desired limit. But we can use Law 4 for the one-sided
limits:
lim f f sxd tsxdg − lim2 f sxd ! lim2 tsxd − 2 ! s22d − 24
x l 12
x l1
x l1
lim f f sxd tsxdg − lim1 f sxd ! lim1 tsxd − 2 ! s21d − 22
x l 11
x l1
x l1
The left and right limits aren’t equal, so lim x l 1 f f sxd tsxdg does not exist.
(c) The graphs show that
lim f sxd < 1.4
xl2
and
lim tsxd − 0
xl2
Because the limit of the denominator is 0, we can’t use Law 5. The given limit does
not exist because the denominator approaches 0 while the numerator approaches a
nonzero number.
n
If we use the Product Law repeatedly with tsxd − f sxd, we obtain the following law.
Power Law
f x la
g
6. lim f f sxdg n − lim f sxd n
x la
where n is a positive integer
A similar property, which you are asked to prove in Exercise 2.5.69, holds for roots:
Root Law
n
n lim f sxd
f sxd − s
7. lim s
x la
x la
where n is a positive integer
f sxd . 0.g
fIf n is even, we assume that xlim
la
In applying these seven limit laws, we need to use two special limits:
8. lim c − c
xla
9. lim x − a
xla
These limits are obvious from an intuitive point of view (state them in words or draw
graphs of y − c and y − x), but proofs based on the precise definition are requested in
Exercises 2.4.23–24.
If we now put f sxd − x in Law 6 and use Law 9, we get a useful special limit for
power functions.
10. lim x n − a n
xla
where n is a positive integer
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SECTION 2.3
Newton and Limits
Isaac Newton was born on Christmas
Day in 1642, the year of Galileo’s
death. When he entered Cambridge
University in 1661 Newton didn’t
know much mathematics, but he
learned quickly by reading Euclid and
Descartes and by attending the lectures of Isaac Barrow. Cambridge was
closed because of the plague from
1665 to 1666, and Newton returned
home to reflect on what he had
learned. Those two years were amazingly productive for at that time he
made four of his major discoveries:
(1) his representation of functions as
sums of infinite series, including the
binomial theorem; (2) his work on differential and integral calculus; (3) his
laws of motion and law of universal
gravitation; and (4) his prism experiments on the nature of light and color.
Because of a fear of controversy and
criticism, he was reluctant to publish
his discoveries and it wasn’t until
1687, at the urging of the astronomer
Halley, that Newton published Principia Mathematica. In this work, the
greatest scientific treatise ever written, Newton set forth his version of
calculus and used it to investigate
mechanics, fluid dynamics, and wave
motion, and to explain the motion
of planets and comets.
The beginnings of calculus are
found in the calculations of areas and
volumes by ancient Greek scholars
such as Eudoxus and Archimedes.
Although aspects of the idea of a
limit are implicit in their “method of
exhaustion,” Eudoxus and Archimedes
never explicitly formulated the concept of a limit. Likewise, mathematicians such as Cavalieri, Fermat, and
Barrow, the immediate precursors of
Newton in the development of calculus, did not actually use limits. It was
Isaac Newton who was the first to talk
explicitly about limits. He explained
that the main idea behind limits is
that quantities “approach nearer than
by any given difference.” Newton
stated that the limit was the basic
concept in calculus, but it was left to
later mathematicians like Cauchy to
clarify his ideas about limits.
Calculating Limits Using the Limit Laws
97
If we put f sxd − x in Law 7 and use Law 9, we get a similar special limit for roots.
(For square roots the proof is outlined in Exercise 2.4.37.)
n
n
11. lim s
x −s
a
xla
where n is a positive integer
(If n is even, we assume that a . 0.)
EXAMPLE 2 Evaluate the following limits and justify each step.
x 3 1 2x 2 2 1
x l 22
5 2 3x
(b) lim
(a) lim s2x 2 2 3x 1 4d
x l5
SOLUTION
(a) lim s2x 2 2 3x 1 4d − lim s2x 2 d 2 lim s3xd 1 lim 4
x l5
x l5
x l5
x l5
(by Laws 2 and 1)
− 2 lim x 2 2 3 lim x 1 lim 4
(by 3)
− 2s5 2 d 2 3s5d 1 4
(by 10, 9, and 8)
x l5
x l5
x l5
− 39
(b) We start by using Law 5, but its use is fully justified only at the final stage when we
see that the limits of the numerator and denominator exist and the limit of the denominator is not 0.
lim sx 3 1 2x 2 2 1d
x l 22
x 3 1 2x 2 2 1
lim
−
lim s5 2 3xd
x l 22
5 2 3x
x l 22
lim x 3 1 2 lim x 2 2 lim 1
x l 22
x l 22
− x l 22
lim 5 2 3 lim x
x l 22
−
x l 22
s22d3 1 2s22d2 2 1
5 2 3s22d
−2
(by Law 5)
(by 1, 2, and 3)
(by 10, 9, and 8)
1
11
n
■ Evaluating Limits by Direct Substitution
In Example 2(a) we determined that lim x l 5 f sxd − 39, where f sxd − 2x 2 2 3x 1 4.
Notice that f s5d − 39; in other words, we would have gotten the correct result simply by
substituting 5 for x. Similarly, direct substitution provides the correct answer in part (b).
The functions in Example 2 are a polynomial and a rational function, respectively, and
similar use of the Limit Laws proves that direct substitution always works for such functions (see Exercises 59 and 60). We state this fact as follows.
Direct Substitution Property If f is a polynomial or a rational function and a is
in the domain of f , then
lim f sxd − f sad
x la
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98
CHAPTER 2
Limits and Derivatives
Functions that have the Direct Substitution Property are called continuous at a and
will be studied in Section 2.5. However, not all limits can be evaluated initially by direct
substitution, as the following examples show.
x2 2 1
.
xl1 x 2 1
EXAMPLE 3 Find lim
SOLUTION Let f sxd − sx 2 2 1dysx 2 1d. We can’t find the limit by substituting x − 1
because f s1d isn’t defined. Nor can we apply the Quotient Law, because the limit of
the denominator is 0. Instead, we need to do some preliminary algebra. We factor the
numerator as a difference of squares:
x2 2 1
sx 2 1dsx 1 1d
−
x21
x21
Notice that in Example 3 we do not
have an infinite limit even though the
denominator approaches 0 as x l 1.
When both numerator and denominator approach 0, the limit may be infinite or it may be some finite value.
The numerator and denominator have a common factor of x 2 1. When we take the
limit as x approaches 1, we have x ± 1 and so x 2 1 ± 0. Therefore we can cancel the
common factor, x 2 1, and then compute the limit by direct substitution as follows:
x2 2 1
sx 2 1dsx 1 1d
− lim
xl1 x 2 1
xl1
x21
lim
− lim sx 1 1d − 1 1 1 − 2
xl1
The limit in this example arose in Example 2.1.1 in finding the tangent to the parabola
y − x 2 at the point s1, 1d.
n
y
y=ƒ
3
2
NOTE In Example 3 we were able to compute the limit by replacing the given function
f sxd − sx 2 2 1dysx 2 1d by a simpler function, tsxd − x 1 1, that has the same limit.
This is valid because f sxd − tsxd except when x − 1, and in computing a limit as x
approaches 1 we don’t consider what happens when x is actually equal to 1. In general,
we have the following useful fact.
If f sxd − tsxd when x ± a, then lim f sxd − lim tsxd, provided the limits exist.
x la
xla
1
0
1
2
3
x
x l1
y
y=©
3
2
1
0
1
2
3
EXAMPLE 4 Find lim tsxd where
x
FIGURE 2
The graphs of the functions f (from
Example 3) and t (from Example 4)
tsxd −
H
x 1 1 if x ± 1
!
if x − 1
SOLUTION Here t is defined at x − 1 and ts1d − !, but the value of a limit as x
approaches 1 does not depend on the value of the function at 1. Since tsxd − x 1 1
for x ± 1, we have
lim tsxd − lim sx 1 1d − 2
xl1
xl1
n
Note that the values of the functions in Examples 3 and 4 are identical except when
x − 1 (see Figure 2) and so they have the same limit as x approaches 1.
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SECTION 2.3
Calculating Limits Using the Limit Laws
99
s3 1 hd2 2 9
.
hl0
h
EXAMPLE 5 Evaluate lim
SOLUTION If we define
Fshd −
s3 1 hd2 2 9
h
then, as in Example 3, we can’t compute lim h l 0 Fshd by letting h − 0 because Fs0d is
undefined. But if we simplify Fshd algebraically, we find that
Fshd −
−
s9 1 6h 1 h 2 d 2 9
6h 1 h 2
−
h
h
hs6 1 hd
−61h
h
(Recall that we consider only h ± 0 when letting h approach 0.) Thus
s3 1 hd2 2 9
− lim s6 1 hd − 6
hl0
hl0
h
lim
n
st 2 1 9 2 3
.
tl0
t2
EXAMPLE 6 Find lim
SOLUTION We can’t apply the Quotient Law immediately because the limit of the
denominator is 0. Here the preliminary algebra consists of rationalizing the numerator:
st 2 1 9 2 3
st 2 1 9 2 3 st 2 1 9 1 3
− lim
!
2
tl0
t
tl0
t2
st 2 1 9 1 3
lim
st 2 1 9d 2 9
t l 0 t 2 (st 2 1 9 1 3)
− lim
t2
t l 0 t (st 2 1 9 1 3)
− lim
− lim
tl0
−
2
1
st 1 9 1 3
2
1
slim st 2 1 9d 1 3
t l0
−
(Here we use several properties
of limits: 5, 1, 7, 8, 10.)
1
1
−
313
6
This calculation confirms the guess that we made in Example 2.2.1.
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n
100
CHAPTER 2
Limits and Derivatives
■ Using One-Sided Limits
Some limits are best calculated by first finding the left- and right-hand limits. The following theorem is a reminder of what we discovered in Section 2.2. It says that a twosided limit exists if and only if both of the one-sided limits exist and are equal.
1 Theorem lim f sxd − L
lim f sxd − L − lim1 f sxd
if and only if
xla
x l a2
x la
When computing one-sided limits, we use the fact that the Limit Laws also hold for
one-sided limits.
EXAMPLE 7 Show that lim | x | − 0.
xl0
SOLUTION Recall that
The result of Example 7 looks plausible
from Figure 3.
y
H
if x > 0
x
| x | − 2x if x , 0
| |
Since x − x for x . 0, we have
| |
lim x − lim1 x − 0
x l 01
y=| x|
| |
x l0
For x , 0 we have x − 2x and so
| |
lim x − lim2 s2xd − 0
x l 02
0
x
x l0
Therefore, by Theorem 1,
| |
lim x − 0
FIGURE 3
xl0
n
EXAMPLE 8 Prove that lim | | does not exist.
x
x
xl0
| |
| |
SOLUTION Using the facts that x − x when x . 0 and x − 2x when x , 0,
we have
y=
y
|x|
x
lim
| x | − lim x − lim 1 − 1
lim
| x | − lim 2x − lim s21d − 21
x l 01
1
0
FIGURE 4
_1
x l 02
x
x
x
x l 01 x
x l 02
x l 01
x
x l 02
Since the right- and left-hand limits are different, it follows from Theorem 1 that
lim x l 0 x yx does not exist. The graph of the function f sxd − x yx is shown in
Figure 4 and supports the one-sided limits that we found.
| |
| |
EXAMPLE 9 If
f sxd −
H
sx 2 4
8 2 2x
n
if x . 4
if x , 4
determine whether lim x l 4 f sxd exists.
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SECTION 2.3
Calculating Limits Using the Limit Laws
101
SOLUTION Since f sxd − sx 2 4 for x . 4, we have
It is shown in Example 2.4.4 that
lim x l 01 sx − 0.
lim f sxd − lim1 s x 2 4 − s4 2 4 − 0
x l 41
x l4
Since f sxd − 8 2 2x for x , 4, we have
y
lim f sxd − lim2 s8 2 2xd − 8 2 2 ? 4 − 0
x l 42
x l4
The right- and left-hand limits are equal. Thus the limit exists and
0
x
4
lim f sxd − 0
xl4
FIGURE 5
The graph of f is shown in Figure 5.
Other notations for v x b are fxg and
EXAMPLE 10 The greatest integer function is defined by v x b − the largest integer
that is less than or equal to x. (For instance, v4 b − 4, v 4.8b − 4, v! b − 3, vs2 b − 1,
v212 b − 21.) Show that lim x l3 v x b does not exist.
:x;. The greatest integer function is
sometimes called the floor function.
y
SOLUTION The graph of the greatest integer function is shown in Figure 6. Since
v x b − 3 for 3 < x , 4, we have
4
3
lim v x b − lim1 3 − 3
x l 31
y=[ x]
2
1
2
3
4
5
x l3
Since v x b − 2 for 2 < x , 3, we have
1
0
n
lim v x b − lim2 2 − 2
x l 32
x
x l3
Because these one-sided limits are not equal, lim xl3 v x b does not exist by Theorem 1. n
■ The Squeeze Theorem
FIGURE 6
The following two theorems describe how the limits of functions are related when the
values of one function are greater than (or equal to) those of another. Their proofs can be
found in Appendix F.
Greatest integer function
2 Theorem If f sxd < tsxd when x is near a (except possibly at a) and the limits
of f and t both exist as x approaches a, then
lim f sxd < lim tsxd
xla
y
h
g
L
f
0
FIGURE 7
a
x
xla
3 The Squeeze Theorem If f sxd < tsxd < hsxd when x is near a (except
possibly at a) and
lim f sxd − lim hsxd − L
xla
then
xla
lim tsxd − L
xla
The Squeeze Theorem, which is sometimes called the Sandwich Theorem or the
Pinching Theorem, is illustrated by Figure 7. It says that if tsxd is squeezed between f sxd
and hsxd near a, and if f and h have the same limit L at a, then t is forced to have the same
limit L at a.
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102
CHAPTER 2
Limits and Derivatives
EXAMPLE 11 Show that lim x 2 sin
xl0
1
− 0.
x
SOLUTION First note that we cannot rewrite the limit as the product of the
limits lim x l 0 x 2 and lim x l 0 sins1yxd because lim x l 0 sins1yxd does not exist (see
Example 2.2.5).
We can find the limit by using the Squeeze Theorem. To apply the Squeeze Theorem
we need to find a function f smaller than tsxd − x 2 sins1yxd and a function h bigger
than t such that both f sxd and hsxd approach 0 as x l 0. To do this we use our knowledge of the sine function. Because the sine of any number lies between 21 and 1, we
can write
4
1
<1
x
21 < sin
Any inequality remains true when multiplied by a positive number. We know that
x 2 > 0 for all x and so, multiplying each side of the inequalities in (4) by x 2, we get
y
y=≈
2x 2 < x 2 sin
1
< x2
x
as illustrated by Figure 8. We know that
x
0
lim x 2 − 0
xl0
Taking f sxd − 2x 2, tsxd − x 2 sins1yxd, and hsxd − x 2 in the Squeeze Theorem, we
obtain
y=_≈
FIGURE 8
1
−0
x
lim x 2 sin
2
y − x sins1yxd
2.3
lim s2x 2 d − 0
and
xl0
xl0
n
Exercises
lim f sxd − 4
xl2
x l2
lim tsxd − 22
xl 2
lim hsxd − 0
xl2
(a) lim f f sxd 1 5tsxdg
(b) lim f tsxdg
(c) lim sf sxd
(d) lim
3f sxd
tsxd
tsxd
(f ) lim
tsxd hsxd
f sxd
xl2
xl2
x l 2 hsxd
xl2
(a) lim f f sxd 1 tsxdg
(b) lim f f sxd 2 tsxdg
(c) lim f f sxd tsxdg
f sxd
(d) lim
x l 3 tsxd
x l2
x l 21
1
1
3
2. The graphs of f and t are given. Use them to evaluate each
limit, if it exists. If the limit does not exist, explain why.
y=©
y=ƒ
0
xl2
xl2
x l 21
y
y
find the limits that exist. If the limit does not exist, explain
why.
(e) lim
(f ) f s21d 1 lim tsxd
(e) lim fx 2 f sxdg
1. Given that
x
1
0
1
x
3–9 Evaluate the limit and justify each step by indicating the
appropriate Limit Law(s).
3. lim s4x 2 2 5xd
4. lim s2x 3 1 6x 2 2 9d
5. lim sv 2 1 2vds2v 3 2 5d
6. lim
7. lim s9 2 u 3 1 2u 2
3
8. lim s
x 1 5 s2x 2 2 3xd
x l5
xl 23
v l2
u l 22
xl0
9. lim
tl 21
S
5
4
2t 2 t
5t 2 1 4
D
tl7
3t 2 1 1
t 2 5t 1 2
2
xl3
3
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SECTION 2.3
; 36. (a) Use a graph of
10. (a) What is wrong with the following equation?
2
x 1x26
−x13
x22
to estimate the value of lim x l 0 f sxd to two decimal
places.
(b) Use a table of values of f sxd to estimate the limit to
four decimal places.
(c) Use the Limit Laws to find the exact value of the limit.
2
lim
x 1x26
− lim sx 1 3d
xl2
x22
is correct.
; 37. Use the Squeeze Theorem to show that
11–34 Evaluate the limit, if it exists.
t 2 2 2t 2 8
tl4
t24
14. lim
x 2 1 5x 1 4
x l2
x22
16. lim
2
x2 2 x 2 6
x l 22 3x 2 1 5x 2 2
18. lim
t 3 2 27
tl3 t2 2 9
20.
lim sx 3 1 x 2 sin
xl0
2x 2 1 9x 2 5
x l 25
x 2 2 25
17. lim
19. lim
lim
u11
sh 2 3d 2 9
h
22. lim
s9 1 h 2 3
h
24. lim
xl4
40. If 2x < tsxd < x 2 x 1 2 for all x, evaluate lim tsxd.
92x
2
xl1
2
41. Prove that lim x cos − 0.
xl 0
x
4
22x
x l 2 sx 1 2 2 2
42. Prove that lim1 sx e sins!yxd − 0.
xl 0
s22 1 hd21 1 2 21
hl0
h
26. lim
S
Illustrate by graphing the functions f, t, and h (in the notation of the Squeeze Theorem) on the same screen.
4
x l 9 3 2 sx
1
1
2
x
3
25. lim
x l3 x 2 3
!
−0
x
39. If 4x 2 9 < f sxd < x 2 2 4x 1 7 for x > 0, find lim f sxd.
u l 21 u 3 1 1
2
hl0
; 38. Use the Squeeze Theorem to show that
x 2 1 3x
x l 4 x 2 x 2 12
15. lim
23. lim
Illustrate by graphing the functions f sxd − 2x 2,
tsxd − x 2 cos 20!x, and hsxd − x 2 on the same screen.
x 2 1 3x
x l 23 x 2 2 x 2 12
13. lim
hl 0
xl0
xl 6
xl 22
21. lim
lim x 2 cos 20!x − 0
12. lim (8 2 12 x)
11. lim s3x 2 7d
s3 1 x 2 s3
x
f sxd −
(b) In view of part (a), explain why the equation
xl2
103
Calculating Limits Using the Limit Laws
D
43–48 Find the limit, if it exists. If the limit does not exist,
explain why.
|
|
44.
2x 2 1
2x 3 2 x 2
46.
43. lim ( x 1 4 2 2x)
lim
| x 1 4|
s1 1 t 2 s1 2 t
27. lim
tl0
t
28. lim
4 2 sx
29. lim
x l 16 16x 2 x 2
x 2 2 4x 1 4
30. lim 4
x l 2 x 2 3x 2 2 4
45.
sx 2 1 9 2 5
32. lim
x l24
x14
47. lim2
1
1
2 2
sx 1 hd2
x
34. lim
hl0
h
49. The Signum Function The signum (or sign) function,
denoted by sgn, is defined by
31. lim
tl0
S
1
1
2
t
t s1 1 t
D
sx 1 hd3 2 x 3
33. lim
hl0
h
; 35. (a) Estimate the value of
lim
tl0
1
1
2 2
t
t 1t
x l 24
lim
x l 0.52
xl 0
|
S
|
| |D
1
1
2
x
x
sgn x −
x
x l 0 s1 1 3x 2 1
by graphing the function f sxd − xyss1 1 3x 2 1d.
(b) Make a table of values of f sxd for x close to 0 and guess
the value of the limit.
(c) Use the Limit Laws to prove that your guess is correct.
x l 24
lim
x l 22
48. lim1
xl 0
H
2x 1 8
| |
22 x
21x
S
1
1
2
x
x
| |
D
21 if x , 0
20 if x − 0
21 if x . 0
(a) Sketch the graph of this function.
(b) Find each of the following limits or explain why it does
not exist.
(i) lim1 sgn x
(ii) lim2 sgn x
xl0
xl 0
(iii) lim sgn x
(iv) lim sgn x
xl0
xl 0
|
|
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104
CHAPTER 2
Limits and Derivatives
50. Let tsxd − sgnssin xd.
(a) Find each of the following limits or explain why it does
not exist.
(i) lim1 tsxd
(ii) lim2 tsxd
(iii) lim tsxd
xl0
xl0
(iv) lim1 tsxd
xl0
(v) lim2 tsxd
xl!
(vi) lim tsxd
xl!
xl!
(b) For which values of a does lim x l a tsxd not exist?
(c) Sketch a graph of t.
(ii) lim2 tsxd
x l2
61. If lim
x l2
xl1
(b) Does lim x l 2 tsxd exist?
(c) Sketch the graph of t.
H
52. Let
f sxd −
Bstd −
f sxd
− 5, find the following limits.
x2
f sxd
(a) lim f sxd
(b) lim
xl0
xl0
x
xl0
x2 1 1
if x , 1
sx 2 2d 2 if x > 1
H
63. If
4 2 12 t
if t , 2
st 1 c
if t > 2
f sxd −
tsxd −
x
3
2 2 x2
x23
65. Show by means of an example that lim x l a f f sxd tsxdg may
exist even though neither lim x l a f sxd nor lim x l a tsxd exists.
66. Evaluate lim
s6 2 x 2 2
x l 2 s3 2 x 2 1
xl1
(v) lim1 tsxd
x l2
(b) Sketch the graph of t.
(vi) lim tsxd
xl2
xl2
55. (a) If the symbol v b denotes the greatest integer function
defined in Example 10, evaluate
(i) lim 1 v x b
(ii) lim v x b
(iii) lim v x b
x l 22
x l 22
x l 22.4
(b) If n is an integer, evaluate
(i) lim2 v x b
(ii) lim1 v x b
x ln
3x 2 1 ax 1 a 1 3
x l 22
x2 1 x 2 2
lim
exists? If so, find the value of a and the value of the limit.
68. The figure shows a fixed circle C1 with equation
sx 2 1d2 1 y 2 − 1 and a shrinking circle C2 with radius r
and center the origin. P is the point s0, rd, Q is the upper point
of intersection of the two circles, and R is the point of intersection of the line PQ and the x-axis. What happens to R
as C2 shrinks, that is, as r l 0 1?
xln
y
(c) For what values of a does lim x l a v x b exist?
56. Let f sxd − v cos x b , 2! < x < !.
(a) Sketch the graph of f.
(b) Evaluate each limit, if it exists.
(i) lim f sxd
(ii)
xl0
(iii)
lim
x l s!y2d1
f sxd
P
lim
x l s!y2d2
.
67. Is there a number a such that
(a) Evaluate each of the following, if it exists.
(i) lim2 tsxd
(ii) lim tsxd
(iii) ts1d
x l1
x 2 if x is rational
0 if x is irrational
64. Show by means of an example that lim x l a f f sxd 1 tsxdg may
exist even though neither lim x l a f sxd nor lim x l a tsxd exists.
if x , 1
if x − 1
if 1 , x < 2
if x . 2
(iv) lim2 tsxd
H
prove that lim x l 0 f sxd − 0.
Find the value of c so that lim t l2 Bstd exists.
54. Let
f sxd 2 8
− 10, find lim f sxd.
xl1
x21
62. If lim
(a) Find lim x l12 f sxd and lim x l11 f sxd.
(b) Does lim x l1 f sxd exist?
(c) Sketch the graph of f.
53. Let
expresses the length L of an object as a function of its velocity v with respect to an observer, where L 0 is the length of the
object at rest and c is the speed of light. Find lim v l c2 L and
interpret the result. Why is a left-hand limit necessary?
60. If r is a rational function, use Exercise 59 to show that
lim x l a rsxd − rsad for every number a in the domain of r.
|
(a) Find
(i) lim1 tsxd
L − L 0 s1 2 v 2yc 2
59. If p is a polynomial, show that lim xl a psxd − psad.
x2 1 x 2 6
51. Let tsxd −
.
x22
|
58. In the theory of relativity, the Lorentz contraction formula
f sxd
(iv) lim f sxd
x l !y2
(c) For what values of a does lim x l a f sxd exist?
Q
C™
0
C¡
R
x
57. If f sxd − v x b 1 v 2x b , show that lim x l 2 f sxd exists but is
not equal to f s2d.
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SECTION 2.4
105
The Precise Definition of a Limit
2.4 The Precise Definition of a Limit
The intuitive definition of a limit given in Section 2.2 is inadequate for some purposes
because such phrases as “x is close to 2” and “ f sxd gets closer and closer to L” are vague.
In order to be able to prove conclusively that
lim
xl0
S
x3 1
cos 5x
10,000
D
− 0.0001
or
lim
xl0
sin x
−1
x
we must make the definition of a limit precise.
■ The Precise Definition of a Limit
To motivate the precise definition of a limit, let’s consider the function
f sxd −
H
2x 2 1 if x ± 3
6
if x − 3
Intuitively, it is clear that when x is close to 3 but x ± 3, then f sxd is close to 5, and so
lim x l3 f sxd − 5.
To obtain more detailed information about how f sxd varies when x is close to 3, we
ask the following question:
How close to 3 does x have to be so that f sxd differs from 5 by less than 0.l ?
|
|
|
|
The distance from x to 3 is x 2 3 and the distance from f sxd to 5 is f sxd 2 5 , so our
problem is to find a number # (the Greek letter delta) such that
| f sxd 2 5 | , 0.1
|
| x 2 3 | , # but x ± 3
if
|
If x 2 3 . 0, then x ± 3, so an equivalent formulation of our problem is to find a
number # such that
| f sxd 2 5 | , 0.1 if 0 , | x 2 3 | , #
Notice that if 0 , | x 2 3 | , s0.1dy2 − 0.05, then
| f sxd 2 5 | − | s2x 2 1d 2 5 | − | 2x 2 6 | − 2| x 2 3 | , 2s0.05d − 0.1
that is,
| f sxd 2 5 | , 0.1 if 0 , | x 2 3 | , 0.05
Thus an answer to the problem is given by # − 0.05; that is, if x is within a distance of
0.05 from 3, then f sxd will be within a distance of 0.1 from 5.
If we change the number 0.l in our problem to the smaller number 0.01, then by using
the same method we find that f sxd will differ from 5 by less than 0.01 provided that x
differs from 3 by less than (0.01)y2 − 0.005:
| f sxd 2 5 | , 0.01
if
0 , x 2 3 , 0.005
|
|
| f sxd 2 5 | , 0.001
if
0 , x 2 3 , 0.0005
|
|
Similarly,
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
106
CHAPTER 2
Limits and Derivatives
The numbers 0.1, 0.01, and 0.001 that we have considered are error tolerances that we
might allow. For 5 to be the precise limit of f sxd as x approaches 3, we must not only be
able to bring the difference between f sxd and 5 below each of these three numbers; we
must be able to bring it below any positive number. And, by the same reasoning, we can!
If we write « (the Greek letter epsilon) for an arbitrary positive number, then we find as
before that
| f sxd 2 5 | , «
1
y
ƒ
is in
here
if
|
|
0, x23 ,#−
«
2
This is a precise way of saying that f sxd is close to 5 when x is close to 3 because (1) says
that we can make the values of f sxd within an arbitrary distance « from 5 by restricting
the values of x to be within a distance «y2 from 3 (but x ± 3).
Note that (1) can be rewritten as follows:
5+∑
5
5-∑
3 2 # , x , 3 1 # sx ± 3d
if
0
x
3
3-∂
then
5 2 « , f sxd , 5 1 «
and this is illustrated in Figure 1. By taking the values of x (± 3) to lie in the interval
s3 2 #, 3 1 #d we can make the values of f sxd lie in the interval s5 2 «, 5 1 «d.
Using (1) as a model, we give a precise definition of a limit.
3+∂
when x is in here
(x≠3)
FIGURE 1
2 Precise Definition of a Limit Let f be a function defined on some open
interval that contains the number a, except possibly at a itself. Then we say that
the limit of f sxd as x approaches a is L, and we write
lim f sxd − L
xla
It is traditional to use the Greek letters « and # in the precise definition
of a limit.
if for every number « . 0 there is a number # . 0 such that
if
|
|
|
0, x2a ,#
|
then
|
| f sxd 2 L | , «
|
Since x 2 a is the distance from x to a and f sxd 2 L is the distance from f sxd to
L, and since « can be arbitrarily small, the definition of a limit can be expressed in words
as follows:
lim x l a f sxd − L means that the distance between f sxd and L can be made arbitrarily small by
requiring that the distance from x to a be sufficiently small (but not 0).
Alternatively,
lim x l a f sxd − L means that the values of f sxd can be made as close as we please to L
by requiring x to be close enough to a (but not equal to a).
We can also reformulate Definition 2 in terms of intervals by observing that the inequality x 2 a , # is equivalent to 2# , x 2 a , #, which in turn can be written as
a 2 # , x , a 1 #. Also 0 , x 2 a is true if and only if x 2 a ± 0, that is, x ± a.
Similarly, the inequality f sxd 2 L , « is equivalent to the pair of inequalities
L 2 « , f sxd , L 1 «. Therefore, in terms of intervals, Definition 2 can be stated as
follows:
|
|
|
|
|
|
lim x l a f sxd − L means that for every « . 0 (no matter how small « is) we can find
# . 0 such that if x lies in the open interval sa 2 #, a 1 #d and x ± a, then f sxd lies in
the open interval sL 2 «, L 1 «d.
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SECTION 2.4
107
The Precise Definition of a Limit
We interpret this statement geometrically by representing a function by an arrow diagram as in Figure 2, where f maps a subset of R onto another subset of R.
f
FIGURE 2
x
a
f(a)
ƒ
The definition of limit says that if any small interval sL 2 «, L 1 «d is given around
L, then we can find an interval sa 2 #, a 1 #d around a such that f maps all the points
in sa 2 #, a 1 #d (except possibly a) into the interval sL 2 «, L 1 «d. (See Figure 3.)
f
x
a-∂
FIGURE 3
ƒ
a
a+∂
L-∑
L
L+∑
Another geometric interpretation of limits can be given in terms of the graph of a
function. If « . 0 is given, then we draw the horizontal lines y 5 L 1 « and y 5 L 2 «
and the graph of f. (See Figure 4.) If lim x l a f sxd − L, then we can find a number # . 0
such that if we restrict x to lie in the interval sa 2 #, a 1 #d and take x ± a, then the
curve y 5 f sxd lies between the lines y 5 L 2 « and y − L 1 «. (See Figure 5.) You can
see that if such a # has been found, then any smaller # will also work.
It is important to realize that the process illustrated in Figures 4 and 5 must work for
every positive number «, no matter how small it is chosen. Figure 6 shows that if a
smaller « is chosen, then a smaller # may be required.
y=ƒ
y
L
y
y=L+∑
ƒ
is in
here
∑
∑
FIGURE 4
L+∑
∑
L
∑
y=L-∑
0
y
y=L+∑
x
0
a-∂
FIGURE 5
y=L-∑
L-∑
y=L-∑
a
y=L+∑
a
0
x
a+∂
a-∂
when x is in here
(x≠a)
a
x
a+∂
FIGURE 6
EXAMPLE 1 Since f sxd − x 3 2 5x 1 6 is a polynomial, we know from the Direct
Substitution Property that lim x l1 f sxd − f s1d − 13 2 5s1d 1 6 − 2. Use a graph to
find a number # such that if x is within # of 1, then y is within 0.2 of 2, that is,
if
|x 2 1| , #
then
| sx 2 5x 1 6d 2 2 | , 0.2
3
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108
CHAPTER 2
Limits and Derivatives
In other words, find a number # that corresponds to « 5 0.2 in the definition of a limit
for the function f sxd 5 x 3 2 5x 1 6 with a 5 1 and L 5 2.
15
SOLUTION A graph of f is shown in Figure 7; we are interested in the region near the
point s1, 2d. Notice that we can rewrite the inequality
| sx 2 5x 1 6d 2 2 | , 0.2
3
3
_3
FIGURE 7
So we need to determine the values of x for which the curve y 5 x 3 2 5x 1 6 lies
between the horizontal lines y 5 1.8 and y 5 2.2. Therefore we graph the curves
y 5 x 3 2 5x 1 6, y 5 1.8, and y 5 2.2 near the point s1, 2d in Figure 8. We estimate
that the x-coordinate of the point of intersection of the line y 5 2.2 and the curve
y 5 x 3 2 5x 1 6 is about 0.911. Similarly, y 5 x 3 2 5x 1 6 intersects the line
y 5 1.8 when x < 1.124. So, rounding toward 1 to be safe, we can say that
2.3
y=2.2
y=˛-5x+6
(1, 2)
if
y=1.8
1.2
FIGURE 8
1.8 , x 3 2 5x 1 6 , 2.2
or equivalently
_5
0.8
1.7
20.2 , sx 3 2 5x 1 6d 2 2 , 0.2
as
0.92 , x , 1.12
then
1.8 , x 3 2 5x 1 6 , 2.2
This interval s0.92, 1.12d is not symmetric about x 5 1. The distance from x 5 1 to the
left endpoint is 1 2 0.92 5 0.08 and the distance to the right endpoint is 0.12. We can
choose # to be the smaller of these numbers, that is, # − 0.08. Then we can rewrite our
inequalities in terms of distances as follows:
| x 2 1 | , 0.08
if
| sx 2 5x 1 6d 2 2 | , 0.2
3
then
This just says that by keeping x within 0.08 of 1, we are able to keep f sxd within 0.2
of 2.
Although we chose # − 0.08, any smaller positive value of # would also have
worked.
n
The graphical procedure used in Example 1 gives an illustration of the definition for
« 5 0.2, but it does not prove that the limit is equal to 2. A proof has to provide a # for
every «.
In proving limit statements it may be helpful to think of the definition of limit as a
challenge. First it challenges you with a number «. Then you must be able to produce a
suitable #. You have to be able to do this for every « . 0, not just a particular «.
Imagine a contest between two people, A and B, and imagine yourself to be B. Person A stipulates that the fixed number L should be approximated by the values of f sxd
to within a degree of accuracy « (say, 0.01). Person B then responds by finding a number # such that if 0 , x 2 a , #, then f sxd 2 L , «. Then A may become more
exacting and challenge B with a smaller value of « (say, 0.0001). Again B has to
respond by finding a corresponding #. Usually the smaller the value of «, the smaller
the corresponding value of # must be. If B always wins, no matter how small A makes
«, then lim x l a f sxd − L.
|
|
|
|
EXAMPLE 2 Prove that lim s4x 2 5d − 7.
x l3
SOLUTION
1. Preliminary analysis of the problem (guessing a value for #). Let « be a given
positive number. We want to find a number # such that
if
|
|
0, x23 ,#
then
| s4x 2 5d 2 7 | , «
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SECTION 2.4
Cauchy and Limits
After the invention of calculus in the
17th century, there followed a period
of free development of the subject
in the 18th century. Mathematicians
like the Bernoulli brothers and Euler
were eager to exploit the power of
calculus and boldly explored the consequences of this new and wonderful
mathematical theory without worrying too much about whether their
proofs were completely correct.
The 19th century, by contrast,
was the Age of Rigor in mathematics.
There was a movement to go back to
the foundations of the subject—to
provide careful definitions and rigorous proofs. At the forefront of this
movement was the French mathematician Augustin-Louis Cauchy (1789–
1857), who started out as a military
engineer before becoming a mathematics professor in Paris. Cauchy
took Newton’s idea of a limit, which
was kept alive in the 18th century
by the French mathematician Jean
d’Alembert, and made it more precise.
His definition of a limit reads as follows: “When the successive values
attributed to a variable approach
indefinitely a fixed value so as to end
by differing from it by as little as one
wishes, this last is called the limit of all
the others.” But when Cauchy used
this definition in examples and proofs,
he often employed delta-epsilon
inequalities similar to the ones in this
section. A typical Cauchy proof starts
with: “Designate by # and « two very
small numbers; . . .” He used « because
of the correspondence between epsilon and the French word erreur and
# because delta corresponds to différence. Later, the German mathematician Karl Weierstrass (1815–1897)
stated the definition of a limit exactly
as in our Definition 2.
|
| |
| |
The Precise Definition of a Limit
|
|
109
|
But s4x 2 5d 2 7 5 4x 2 12 5 4sx 2 3d 5 4 x 2 3 . Therefore we want #
such that
if
0, x23 ,#
then
4 x23 ,«
that is,
if
|
|
|
|
|
«
|x 2 3| , 4
then
0, x23 ,#
|
This suggests that we should choose # 5 «y4.
2. Proof (showing that this # works). Given « . 0, choose # 5 «y4. If
0 , x 2 3 , #, then
|
Thus
|
«
| s4x 2 5d 2 7 | − | 4x 2 12 | − 4| x 2 3 | , 4# − 4 4
SD
if
|
|
0, x23 ,#
−«
| s4x 2 5d 2 7 | , «
then
Therefore, by the definition of a limit,
lim s4x 2 5d − 7
x l3
This example is illustrated by Figure 9.
y
y=4x-5
7+∑
7
7-∑
0
3-∂
FIGURE 9
x
3
3+∂
n
Note that in the solution of Example 2 there were two stages—guessing and proving.
We made a preliminary analysis that enabled us to guess a value for #. But then in the
second stage we had to go back and prove in a careful, logical fashion that we had made
a correct guess. This procedure is typical of much of mathematics. Sometimes it is necessary to first make an intelligent guess about the answer to a problem and then prove that
the guess is correct.
EXAMPLE 3 Prove that lim x 2 − 9.
xl3
SOLUTION
1. Guessing a value for #. Let « . 0 be given. We have to find a number # . 0
such that
if
0, x23 ,#
then
x2 2 9 , «
|
|
|
|
To connect | x 2 9 | with | x 2 3 | we write | x 2 9 | 5 | sx 1 3dsx 2 3d |. Then
2
we want
if
2
|
|
0, x23 ,#
then
| x 1 3 || x 2 3 | , «
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110
CHAPTER 2
Limits and Derivatives
|
|
Notice that if we can find a positive constant C such that x 1 3 , C, then
| x 1 3 || x 2 3 | , C | x 2 3 |
and we can make C | x 2 3 | , « by taking | x 2 3 | , «yC, so we could
choose # − «yC.
We can find such a number C if we restrict x to lie in some interval centered at 3.
In fact, since we are interested only in values of x that are close to 3, it is reasonable to
assume that x is within a distance l from 3, that is, x 2 3 , 1. Then 2 , x , 4, so
5 , x 1 3 , 7. Thus we have x 1 3 , 7, and so C 5 7 is a suitable choice for the
constant.
But now there are two restrictions on x 2 3 , namely
|
|
|
|
|x 2 3| , 1
|
|
«
«
|x 2 3| , C 5 7
and
To make sure that both of these inequalities are satisfied, we take # to be the smaller of
the two numbers 1 and «y7. The notation for this is # − minh1, «y7j.
2. Showing that this # works. Given « . 0, let # − minh1, «y7j. If
0 , x 2 3 , #, then x 2 3 , 1 ? 2 , x , 4 ? x 1 3 , 7 (as in part l).
We also have x 2 3 , «y7, so
|
|
|
|
|
|
|
|
«
| x 2 9 | − | x 1 3 || x 2 3 | , 7 ? 7 − «
2
This shows that lim x l3 x 2 − 9.
n
■ One-Sided Limits
The intuitive definitions of one-sided limits that were given in Section 2.2 can be precisely reformulated as follows.
3 Precise Definition of Left-Hand Limit
lim f sxd − L
x l a2
if for every number « . 0 there is a number # . 0 such that
if
a2#,x,a
then
| f sxd 2 L | , «
4 Precise Definition of Right-Hand Limit
lim f sxd − L
x la1
if for every number « . 0 there is a number # . 0 such that
if
a,x,a1#
then
| f sxd 2 L | , «
Notice that Definition 3 is the same as Definition 2 except that x is restricted to lie in
the left half sa 2 #, ad of the interval sa 2 #, a 1 #d. In Definition 4, x is restricted to lie
in the right half sa, a 1 #d of the interval sa 2 #, a 1 #d.
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SECTION 2.4
The Precise Definition of a Limit
111
EXAMPLE 4 Use Definition 4 to prove that lim1 sx − 0.
xl0
SOLUTION
1. Guessing a value for #. Let « be a given positive number. Here a 5 0 and L 5 0,
so we want to find a number # such that
that is,
if
0,x,#
then
| sx 2 0 | , «
if
0,x,#
then
sx , «
or, squaring both sides of the inequality sx , «, we get
if
0,x,#
x , «2
then
This suggests that we should choose # 5 « 2.
2. Showing that this # works. Given « . 0, let # 5 « 2. If 0 , x , #, then
sx , s# 5 s« 2 5 «
| sx 2 0 | , «
so
According to Definition 4, this shows that lim x l 01 sx − 0.
n
■ The Limit Laws
As the preceding examples show, it is not always easy to prove that limit statements are
true using the «, # definition. In fact, if we had been given a more complicated function
such as f sxd 5 s6x 2 2 8x 1 9dys2x 2 2 1d, a proof would require a great deal of ingenuity. Fortunately this is unnecessary because the Limit Laws stated in Section 2.3 can be
proved using Definition 2, and then the limits of complicated functions can be found
rigorously from the Limit Laws without resorting to the definition directly.
For instance, we prove the Sum Law: If lim x l a f sxd − L and lim x l a tsxd − M both
exist, then
lim f f sxd 1 tsxdg − L 1 M
xla
The remaining laws are proved in the exercises and in Appendix F.
PROOF OF THE SUM LAW Let « . 0 be given. We must find # . 0 such that
if
Triangle Inequality:
|a 1 b| < |a| 1 |b|
(See Appendix A.)
|
|
0, x2a ,#
then
| f sxd 1 tsxd 2 sL 1 Md | , «
Using the Triangle Inequality we can write
| f sxd 1 tsxd 2 sL 1 Md | 5 | s f sxd 2 Ld 1 stsxd 2 Md |
< | f sxd 2 L | 1 | tsxd 2 M |
We make | f sxd 1 tsxd 2 sL 1 Md | less than « by making each of the terms
| f sxd 2 L | and | tsxd 2 M | less than «y2.
5
Since «y2 . 0 and lim x l a f sxd − L, there exists a number # 1 . 0 such that
if
|
|
0 , x 2 a , #1
then
«
| f sxd 2 L | , 2
Similarly, since lim x l a tsxd − M, there exists a number # 2 . 0 such that
if
|
|
0 , x 2 a , #2
then
«
| tsxd 2 M | , 2
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112
CHAPTER 2
Limits and Derivatives
Let # − minh#1, #2j, the smaller of the numbers # 1 and # 2. Notice that
|
if
|
|
|
|
and
| tsxd 2 M | , 2
0 , x 2 a , # then 0 , x 2 a , # 1
«
| f sxd 2 L | , 2
and so
|
and 0 , x 2 a , # 2
«
Therefore, by (5),
| f sxd 1 tsxd 2 sL 1 Md | < | f sxd 2 L | 1 | tsxd 2 M |
,
«
«
1 5«
2
2
To summarize,
if
|
|
0, x2a ,#
then
| f sxd 1 tsxd 2 sL 1 Md | , «
Thus, by the definition of a limit,
lim f f sxd 1 tsxdg − L 1 M
n
xla
■ Infinite Limits
Infinite limits can also be defined in a precise way. The following is a precise version of
Definition 2.2.4.
6 Precise Definition of an Infinite Limit Let f be a function defined on some
open interval that contains the number a, except possibly at a itself. Then
lim f sxd − `
xla
y
means that for every positive number M there is a positive number # such that
y=M
M
0
a-∂
FIGURE 10
a
a+∂
x
|
if
|
0, x2a ,#
f sxd . M
then
This says that the values of f sxd can be made arbitrarily large (larger than any given
number M) by requiring x to be close enough to a (within a distance #, where # depends
on M, but with x ± a). A geometric illustration is shown in Figure 10.
Given any horizontal line y 5 M, we can find a number # . 0 such that if we restrict
x to lie in the interval sa 2 #, a 1 #d but x ± a, then the curve y 5 f sxd lies above the
line y − M. You can see that if a larger M is chosen, then a smaller # may be required.
EXAMPLE 5 Use Definition 6 to prove that lim
1
xl0 x2
− `.
SOLUTION Let M be a given positive number. We want to find a number # such that
if
But
1
.M
x2
&?
| |
0, x ,#
x2 ,
1
M
&?
then
sx 2 ,
1yx 2 . M
Î
1
M
&?
1
| x | , sM
| |
So if we choose # − 1ysM and 0 , x , # − 1ysM , then 1yx 2 . M. This shows
that 1yx 2 l ` as x l 0.
n
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SECTION 2.4
y
a-∂
Similarly, the following is a precise version of Definition 2.2.5. It is illustrated by
Figure 11.
a+∂
a
0
7 Definition Let f be a function defined on some open interval that contains
the number a, except possibly at a itself. Then
x
lim f sxd − 2`
xla
y=N
N
113
The Precise Definition of a Limit
means that for every negative number N there is a positive number ! such that
FIGURE 11
if
|
|
0, x2a ,!
f sxd , N
then
2.4 Exercises
1. Use the given graph of f to find a number ! such that
if
|x 2 1| , !
4. Use the given graph of f sxd 5 x 2 to find a number ! such that
| f sxd 2 1 | , 0.2
then
|x 2 1| , !
if
y
| x 2 1 | , 12
2
then
y
1.2
1
0.8
y=≈
1.5
1
0.5
0
0.7
x
1 1.1
0
2. Use the given graph of f to find a number ! such that
|
|
0, x23 ,d
if
| f s xd 2 2 | , 0.5
then
y
?
1
?
x
; 5. Use a graph to find a number ! such that
|x 2 2| , !
if
then
| sx 1 5 2 3 | , 0.3
2
; 6. Use a graph to find a number ! such that
2.5
Z
if
2
1.5
x2
; 7. For the limit
"
6
Z
,!
then
Z
cos 2 x 2
3
4
Z
, 0.1
lim sx 3 2 3x 1 4d − 6
xl2
0
2.6 3
x
3.8
3. Use the given graph of f sxd − sx to find a number ! such
that
if
|
|
x24 ,!
|
then
y
; 8. For the limit
|
illustrate Definition 2 by finding values of ! that correspond
to « 5 0.5 and « 5 0.1.
; 9. (a) Use a graph to find a number ! such that
if
0
e 2x 2 1
−2
xl0
x
lim
sx 2 2 , 0.4
y=œ„
x
2.4
2
1.6
illustrate Definition 2 by finding values of ! that correspond
to « 5 0.2 and « 5 0.1.
?
4
?
x
2,x,21!
then
1
. 100
lnsx 2 1d
(b) What limit does part (a) suggest is true?
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114
CHAPTER 2
Limits and Derivatives
; 10. Given that lim x l! csc x − `, illustrate Definition 6 by
finding values of # that correspond to (a) M − 500 and
(b) M − 1000.
2
11. A machinist is required to manufacture a circular metal disk
with area 1000 cm2.
(a) What radius produces such a disk?
(b) If the machinist is allowed an error tolerance of 65 cm 2
in the area of the disk, how close to the ideal radius in
part (a) must the machinist control the radius?
(c) In terms of the «, # definition of lim x l a f sxd − L, what
is x? What is f sxd? What is a? What is L? What value
of « is given? What is the corresponding value of #?
; 12. Crystal growth furnaces are used in research to determine
how best to manufacture crystals used in electronic components. For proper growth of a crystal, the temperature must
be controlled accurately by adjusting the input power. Suppose the relationship is given by
T swd − 0.1w 2 1 2.155w 1 20
where T is the temperature in degrees Celsius and w is the
power input in watts.
(a) How much power is needed to maintain the temperature
at 200°C?
(b) If the temperature is allowed to vary from 200°C by
up to 61°C, what range of wattage is allowed for the
input power?
(c) In terms of the «, # definition of lim x l a f sxd − L, what
is x? What is f sxd? What is a? What is L? What value of
« is given? What is the corresponding value of #?
|
|
13. (a) Find a number # such that if x 2 2 , #, then
4x 2 8 , «, where « 5 0.1.
(b) Repeat part (a) with « 5 0.01.
|
|
14. Given that limx l 2 s5x 2 7d − 3, illustrate Definition 2 by
finding values of # that correspond to « 5 0.1, « 5 0.05,
and « 5 0.01.
15–18 Prove the statement using the «, # definition of a limit
and illustrate with a diagram like Figure 9.
15. lim ( 12 x 2 1) − 1
16. lim s2 2 3xd − 24
17. lim s22x 1 1d − 5
18. lim s2x 2 5d − 23
xl4
xl22
x l2
29. lim sx 2 2 4x 1 5d − 1
30. lim sx 2 1 2x 2 7d − 1
31. lim sx 2 1d − 3
32. lim x 3 − 8
xl2
xl2
2
x l 22
xl2
33. Verify that another possible choice of # for showing that
lim x l3 x 2 − 9 in Example 3 is # − min h2, «y8j.
34. Verify, by a geometric argument, that the largest possible
choice of # for showing that lim x l3 x 2 − 9 is
# − s 9 1 « 2 3.
35. (a) For the limit lim x l 1 sx 3 1 x 1 1d − 3, use a graph to
find a value of # that corresponds to « 5 0.4.
(b) By solving the cubic equation x 3 1 x 1 1 5 3 1 «,
find the largest possible value of # that works for any
given « . 0.
(c) Put « 5 0.4 in your answer to part (b) and compare
with your answer to part (a).
36. Prove that lim
1
x l2 x
−
1
.
2
37. Prove that lim sx − sa if a . 0.
F
xla
|
Hint: Use sx 2 sa
| − s|x 1 s|a .
x2a
38. If H is the Heaviside function defined in Section 2.2,
prove, using Definition 2, that lim t l 0 Hstd does not exist.
[Hint: Use an indirect proof as follows. Suppose that the
limit is L. Take « 5 12 in the definition of a limit and try to
arrive at a contradiction.]
39. If the function f is defined by
f sxd −
H
0 if x is rational
1 if x is irrational
prove that lim x l 0 f sxd does not exist.
40. By comparing Definitions 2, 3, and 4, prove Theorem 2.3.1:
lim f sxd − L
xla
if and only if
lim f sxd − L − lim1 f sxd
x l a2
1
. 10,000
sx 1 3d4
x l1
xl9
x 2 2 2x 2 8
−6
xl4
x24
20. lim ( 32 x 2 12 ) − 7
9 2 4x 2
−6
x l21.5 3 1 2x
22.
23. lim x − a
24. lim c − c
xla
2
25. lim x − 0
xl0
| |
27. lim x − 0
xl0
42. Prove, using Definition 6, that lim
lim
xla
26. lim x 3 − 0
xl0
28.
8
lim s
61x −0
x l 261
1
x l23 sx 1 3d4
xl5
21. lim
x la
41. How close to 23 do we have to take x so that
19–32 Prove the statement using the «, # definition of a limit.
19. lim (1 2 13 x) − 22
F
− `.
43. Prove that lim1 ln x − 2`.
xl0
44. Suppose that lim x l a f sxd − ` and lim x l a tsxd − c, where
c is a real number. Prove each statement.
(a) lim f f sxd 1 tsxdg − `
xla
(b) lim f f sxd tsxdg − `
xla
(c) lim f f sxd tsxdg − 2`
xl a
if c . 0
if c , 0
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SECTION 2.5
Continuity
115
2.5 Continuity
■ Continuity of a Function
We noticed in Section 2.3 that the limit of a function as x approaches a can often be
found simply by calculating the value of the function at a. Functions having this property
are called continuous at a. We will see that the mathematical definition of continuity corresponds closely with the meaning of the word continuity in everyday language. (A continuous process is one that takes place without interruption.)
1 Definition A function f is continuous at a number a if
lim f sxd − f sad
xl a
As illustrated in Figure 1, if f is continuous, then the points sx, f sxdd on
the graph of f approach the point
sa, f sadd on the graph. So there is no
gap in the curve.
Notice that Definition l implicitly requires three things if f is continuous at a:
1. f sad is defined (that is, a is in the domain of f )
2. lim f sxd exists
x la
3. lim f sxd − f sad
x la
y
ƒ
approaches
f(a)
y=ƒ
f(a)
0
x
a
as x approaches a
FIGURE 1
y
0
The definition says that f is continuous at a if f sxd approaches f sad as x approaches
a. Thus a continuous function f has the property that a small change in x produces only
a small change in f sxd. In fact, the change in f sxd can be kept as small as we please by
keeping the change in x sufficiently small.
If f is defined near a (in other words, f is defined on an open interval containing a,
except perhaps at a), we say that f is discontinuous at a (or f has a discontinuity at a)
if f is not continuous at a.
Physical phenomena are usually continuous. For instance, the displacement or velocity of a moving vehicle varies continuously with time, as does a person’s height. But
discontinuities do occur in such situations as electric currents. [The Heaviside function,
introduced in Section 2.2, is discontinuous at 0 because lim t l 0 Hstd does not exist.]
Geometrically, you can think of a function that is continuous at every number in an
interval as a function whose graph has no break in it: the graph can be drawn without
removing your pen from the paper.
EXAMPLE 1 Figure 2 shows the graph of a function f. At which numbers is f discontinuous? Why?
1
FIGURE 2
2
3
4
5
x
SOLUTION It looks as if there is a discontinuity when a − 1 because the graph has a
break there. The official reason that f is discontinuous at 1 is that f s1d is not defined.
The graph also has a break when a 5 3, but the reason for the discontinuity is
different. Here, f s3d is defined, but lim x l3 f sxd does not exist (because the left and
right limits are different). So f is discontinuous at 3.
What about a 5 5? Here, f s5d is defined and lim x l5 f sxd exists (because the left and
right limits are the same). But
lim f sxd ± f s5d
xl5
So f is discontinuous at 5.
n
Now let’s see how to detect discontinuities when a function is defined by a formula.
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116
CHAPTER 2
Limits and Derivatives
H
EXAMPLE 2 Where are each of the following functions discontinuous?
x2 2 x 2 2
(a) f sxd 5
x22
(c) f sxd −
H
1
x2
if x ± 0
1
if x − 0
(b) f sxd −
x2 2 x 2 2
x22
if x ± 2
1
if x − 2
(d) f sxd − v x b
SOLUTION
(a) Notice that f s2d is not defined, so f is discontinuous at 2. Later we’ll see why f is
continuous at all other numbers.
(b) Here f s2d 5 1 is defined and
x2 2 x 2 2
sx 2 2dsx 1 1d
− lim
− lim sx 1 1d − 3
x l2
x l2
x l2
x22
x22
lim f sxd − lim
x l2
exists. But
lim f sxd ± f s2d
x l2
so f is not continuous at 2.
(c) Here f s0d 5 1 is defined but
lim f sxd − lim
1
xl0 x2
xl0
does not exist. (See Example 2.2.6.) So f is discontinuous at 0.
(d) The greatest integer function f sxd − v x b has discontinuities at all of the integers because lim x ln v x b does not exist if n is an integer. (See Example 2.3.10 and
Exercise 2.3.55.)
n
Figure 3 shows the graphs of the functions in Example 2. In each case the graph can’t
be drawn without lifting the pen from the paper because a hole or break or jump occurs
in the graph. The kind of discontinuity illustrated in parts (a) and (b) is called removable
because we could remove the discontinuity by redefining f at just the single number 2.
[If we redefine f to be 3 at x − 2, then f is equivalent to the function tsxd − x 1 1,
which is continuous.] The discontinuity in part (c) is called an infinite discontinuity.
The discontinuities in part (d) are called jump discontinuities because the function
“jumps” from one value to another.
y
y
y
y
1
1
1
1
0
1
2
0
x
(a) A removable discontinuity
1
2
x
(b) A removable discontinuity
0
(c) An infinite discontinuity
x
0
1
2
3
x
(d) Jump discontinuities
FIGURE 3
Graphs of the functions in Example 2
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SECTION 2.5
Continuity
117
2 Definition A function f is continuous from the right at a number a if
lim f sxd − f sad
x l a1
and f is continuous from the left at a if
lim f sxd − f sad
x l a2
EXAMPLE 3 At each integer n, the function f sxd − v x b [see Figure 3(d)] is continuous from the right but discontinuous from the left because
lim f sxd − lim1 v xb − n − f snd
x l n1
x ln
lim f sxd − lim2 v x b − n 2 1 ± f snd
but
x l n2
x ln
n
3 Definition A function f is continuous on an interval if it is continuous at
every number in the interval. (If f is defined only on one side of an endpoint of the
interval, we understand continuous at the endpoint to mean continuous from the
right or continuous from the left.)
EXAMPLE 4 Show that the function f sxd − 1 2 s1 2 x 2 is continuous on the
interval f21, 1g.
SOLUTION If 21 , a , 1, then using the Limit Laws from Section 2.3, we have
lim f sxd − lim (1 2 s1 2 x 2 )
xla
xla
− 1 2 lim s1 2 x 2
(by Laws 2 and 8)
− 1 2 s lim s1 2 x 2 d
(by 7)
− 1 2 s1 2 a 2
(by 2, 8, and 10)
xla
xla
y
1
− f sad
y=1-œ„„„„„
1-≈
Thus, by Definition l, f is continuous at a if 21 , a , 1. Similar calculations show that
lim f sxd − 1 − f s21d
x l 211
-1
FIGURE 4
0
1
x
and
lim f sxd − 1 − f s1d
x l 12
so f is continuous from the right at 21 and continuous from the left at 1. Therefore,
according to Definition 3, f is continuous on f21, 1g.
The graph of f is sketched in Figure 4. It is the lower half of the circle
x 2 1 s y 2 1d2 − 1
n
■ Properties of Continuous Functions
Instead of always using Definitions 1, 2, and 3 to verify the continuity of a function as
we did in Example 4, it is often convenient to use the next theorem, which shows how to
build up complicated continuous functions from simple ones.
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118
CHAPTER 2
Limits and Derivatives
4 Theorem If f and t are continuous at a and c is a constant, then the following functions are also continuous at a:
1. f 1 t
2. f 2 t
4. ft
5.
f
t
3. cf
if tsad ± 0
PROOF Each of the five parts of this theorem follows from the corresponding Limit
Law in Section 2.3. For instance, we give the proof of part 1. Since f and t are continuous at a, we have
lim f sxd − f sad
lim tsxd − tsad
and
xla
xla
Therefore
lim s f 1 tdsxd − lim f f sxd 1 tsxdg
xla
xla
− lim f sxd 1 lim tsxd
xla
xla
(by Law 1)
− f sad 1 tsad
− s f 1 tdsad
This shows that f 1 t is continuous at a.
n
It follows from Theorem 4 and Definition 3 that if f and t are continuous on an interval, then so are the functions f 1 t, f 2 t, cf, ft, and (if t is never 0) fyt. The following
theorem was stated in Section 2.3 as the Direct Substitution Property.
5 Theorem
(a) Any polynomial is continuous everywhere; that is, it is continuous on
R − s2`, `d.
(b) Any rational function is continuous wherever it is defined; that is, it is continuous on its domain.
PROOF
(a) A polynomial is a function of the form
Psxd − cn x n 1 cn21 x n21 1 ∙ ∙ ∙ 1 c1 x 1 c0
where c0 , c1, . . . , cn are constants. We know that
lim c0 − c0
xla
and
lim x m − a m
xla
(by Law 8)
m − 1, 2, . . . , n
(by 10)
This equation is precisely the statement that the function f sxd − x m is a continuous
function. Thus, by part 3 of Theorem 4, the function tsxd − cx m is continuous. Since P
is a sum of functions of this form and a constant function, it follows from part 1 of
Theorem 4 that P is continuous.
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SECTION 2.5
Continuity
119
(b) A rational function is a function of the form
f sxd −
Psxd
Qsxd
|
where P and Q are polynomials. The domain of f is D − hx [ R Qsxd ± 0j. We
know from part (a) that P and Q are continuous everywhere. Thus, by part 5 of Theorem 4, f is continuous at every number in D.
n
As an illustration of Theorem 5, observe that the volume of a sphere varies continuously with its radius because the formula Vsrd − 43 !r 3 shows that V is a polynomial
function of r. Likewise, if a ball is thrown vertically into the air with an initial velocity
of 50 ftys, then the height of the ball in feet t seconds later is given by the formula
h − 50t 2 16t 2. Again this is a polynomial function, so the height is a continuous function of the elapsed time, as we might expect.
Knowledge of which functions are continuous enables us to evaluate some limits very
quickly, as the following example shows. Compare it with Example 2.3.2(b).
x 3 1 2x 2 2 1
.
x l 22
5 2 3x
EXAMPLE 5 Find lim
SOLUTION The function
f sxd −
x 3 1 2x 2 2 1
5 2 3x
|
is rational, so by Theorem 5 it is continuous on its domain, which is h x x ± 53 j.
Therefore
x 3 1 2x 2 2 1
lim
− lim f sxd − f s22d
x l22
x l22
5 2 3x
y
−
P(cos ¨, sin ¨)
1
0
¨
(1, 0)
x
FIGURE 5
n
It turns out that most of the familiar functions are continuous at every number in their
domains. For instance, Limit Law 11 in Section 2.3 is exactly the statement that root
functions are continuous.
From the appearance of the graphs of the sine and cosine functions (Figure 1.2.19),
we would certainly guess that they are continuous. We know from the definitions of sin "
and cos " that the coordinates of the point P in Figure 5 are scos ", sin "d. As " l 0, we
see that P approaches the point s1, 0d and so cos " l 1 and sin " l 0. Thus
6
Another way to establish the limits in
(6) is to use the Squeeze Theorem
with the inequality sin " , " (for
" . 0), which is proved in Section 3.3.
s22d3 1 2s22d2 2 1
1
−2
5 2 3s22d
11
lim cos " − 1
"l0
lim sin " − 0
"l0
Since cos 0 − 1 and sin 0 − 0, the equations in (6) assert that the cosine and sine functions are continuous at 0. The addition formulas for cosine and sine can then be used to
deduce that these functions are continuous everywhere (see Exercises 66 and 67).
It follows from part 5 of Theorem 4 that
tan x −
sin x
cos x
is continuous except where cos x − 0. This happens when x is an odd integer multiple
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120
CHAPTER 2
Limits and Derivatives
y
1
3π _π
_ 2
_
π
2
0
π
2
π
3π
2
x
FIGURE 6
y − tan x
The inverse trigonometric functions
are reviewed in Section 1.5.
of !y2, so y − tan x has infinite discontinuities when x − 6!y2, 63!y2, 65!y2, and
so on (see Figure 6).
The inverse function of any continuous one-to-one function is also continuous. (This
fact is proved in Appendix F, but our geometric intuition makes it seem plausible: the
graph of f 21 is obtained by reflecting the graph of f about the line y − x. So if the graph
of f has no break in it, neither does the graph of f 21.) Thus the inverse trigonometric
functions are continuous.
In Section 1.4 we defined the exponential function y − b x so as to fill in the holes in
the graph of y − b x where x is rational. In other words, the very definition of y − b x
makes it a continuous function on R. Therefore its inverse function y − log b x is continuous on s0, `d.
7 Theorem The following types of functions are continuous at every number in
their domains:
• polynomials
• rational functions
• root functions
• trigonometric functions
• inverse trigonometric functions
• exponential functions
• logarithmic functions
EXAMPLE 6 Where is the function f sxd −
ln x 1 tan21 x
continuous?
x2 2 1
SOLUTION We know from Theorem 7 that the function y − ln x is continuous for x . 0
and y − tan21x is continuous on R. Thus, by part 1 of Theorem 4, y − ln x 1 tan21x is
continuous on s0, `d. The denominator, y − x 2 2 1, is a polynomial, so it is continuous
everywhere. Therefore, by part 5 of Theorem 4, f is continuous at all positive numbers
x except where x 2 2 1 − 0 &? x − 61. So f is continuous on the intervals s0, 1d
and s1, `d.
n
EXAMPLE 7 Evaluate lim
sin x
x l ! 2 1 cos x
.
SOLUTION Theorem 7 tells us that y − sin x is continuous. The function in the
denominator, y − 2 1 cos x, is the sum of two continuous functions and is therefore
continuous. Notice that this function is never 0 because cos x > 21 for all x and so
2 1 cos x . 0 everywhere. Thus the ratio
f sxd −
sin x
2 1 cos x
is continuous everywhere. Hence, by the definition of a continuous function,
lim
sin x
x l ! 2 1 cos x
− lim f sxd − f s!d −
x l!
sin !
0
−
−0
2 1 cos !
221
n
Another way of combining continuous functions f and t to get a new continuous
function is to form the composite function f 8 t. This fact is a consequence of the following theorem.
This theorem says that a limit symbol
can be moved through a function symbol if the function is continuous and the
limit exists. In other words, the order of
these two symbols can be reversed.
8 Theorem If f is continuous at b and lim tsxd − b, then lim f s tsxdd − f sbd.
x la
x la
In other words,
lim f stsxdd − f lim tsxd
xla
!
xl a
"
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SECTION 2.5
Continuity
121
Intuitively, Theorem 8 is reasonable because if x is close to a, then tsxd is close to b,
and since f is continuous at b, if tsxd is close to b, then fstsxdd is close to f sbd. A proof
of Theorem 8 is given in Appendix F.
EXAMPLE 8 Evaluate lim arcsin
x l1
S
D
1 2 sx
.
12x
SOLUTION Because arcsin is a continuous function, we can apply Theorem 8:
lim arcsin
x l1
S
1 2 sx
12x
D
S
D
S ( )(
S
D
− arcsin lim
1 2 sx
12x
− arcsin lim
1 2 sx
1 2 sx 1 1 sx )
x l1
x l1
− arcsin lim
D
1
x l 1 1 1 sx
− arcsin
1
!
−
2
6
n
n
Let’s now apply Theorem 8 in the special case where f sxd − s
x , with n being a positive integer. Then
and
!
n
tsxd
f stsxdd − s
"
n lim tsxd
f lim tsxd − s
xla
xla
If we put these expressions into Theorem 8, we get
n
n lim tsxd
lim s
tsxd − s
xla
xla
and so Limit Law 7 has now been proved. (We assume that the roots exist.)
9 Theorem If t is continuous at a and f is continuous at tsad, then the composite function f 8 t given by s f 8 tds xd − f stsxdd is continuous at a.
This theorem is often expressed informally by saying “a continuous function of a
continuous function is a continuous function.”
PROOF Since t is continuous at a, we have
lim tsxd − tsad
xla
Since f is continuous at b − tsad, we can apply Theorem 8 to obtain
lim f stsxdd − f stsadd
xla
which is precisely the statement that the function hsxd − f s tsxdd is continuous at a;
that is, f 8 t is continuous at a.
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n
122
CHAPTER 2
Limits and Derivatives
EXAMPLE 9 Where are the following functions continuous?
(a) hsxd − sinsx 2 d
(b) Fsxd − lns1 1 cos xd
SOLUTION
(a) We have hsxd − f stsxdd, where
2
tsxd − x 2
_10
10
_6
FIGURE 7
y − lns1 1 cos xd
and
f sxd − sin x
We know that t is continuous on R since it is a polynomial, and f is also continuous
everywhere. Thus h − f 8 t is continuous on R by Theorem 9.
(b) We know from Theorem 7 that f sxd − ln x is continuous and tsxd − 1 1 cos x is
continuous (because both y − 1 and y − cos x are continuous). Therefore, by Theorem 9, Fsxd − f stsxdd is continuous wherever it is defined. The expression ln s1 1 cos xd
is defined when 1 1 cos x . 0, so it is undefined when cos x − 21, and this happens
when x − 6!, 63!, . . . . Thus F has discontinuities when x is an odd multiple of !
and is continuous on the intervals between these values (see Figure 7).
n
■ The Intermediate Value Theorem
An important property of continuous functions is expressed by the following theorem,
whose proof is found in more advanced books on calculus.
10 The Intermediate Value Theorem Suppose that f is continuous on the
closed interval fa, bg and let N be any number between f sad and f sbd, where
f sad ± f sbd. Then there exists a number c in sa, bd such that f scd − N.
The Intermediate Value Theorem states that a continuous function takes on every intermediate value between the function values f sad and f sbd. It is illustrated by Figure 8. Note
that the value N can be taken on once [as in part (a)] or more than once [as in part (b)].
y
y
f(b)
f(b)
y=ƒ
N
N
y=ƒ
f(a)
0
a
f(a)
y=N
f(b)
a
FIGURE 9
x
0
a c¡
c™
c£
b
x
(b)
FIGURE 8
y=ƒ
N
0
c b
(a)
y
f(a)
b
x
If we think of a continuous function as a function whose graph has no hole or break,
then it is easy to believe that the Intermediate Value Theorem is true. In geometric terms
it says that if any horizontal line y − N is given between y − f sad and y − f sbd as in Figure 9, then the graph of f can’t jump over the line. It must intersect y − N somewhere.
It is important that the function f in Theorem 10 be continuous. The Intermediate
Value Theorem is not true in general for discontinuous functions (see Exercise 52).
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SECTION 2.5
Continuity
123
One use of the Intermediate Value Theorem is in locating solutions of equations as in
the following example.
EXAMPLE 10 Show that there is a solution of the equation
4x 3 2 6x 2 1 3x 2 2 − 0
between 1 and 2.
SOLUTION Let f sxd − 4x 3 2 6x 2 1 3x 2 2. We are looking for a solution of the
given equation, that is, a number c between 1 and 2 such that f scd − 0. Therefore we
take a − 1, b − 2, and N − 0 in Theorem 10. We have
f s1d − 4 2 6 1 3 2 2 − 21 , 0
f s2d − 32 2 24 1 6 2 2 − 12 . 0
and
Thus f s1d , 0 , f s2d; that is, N − 0 is a number between f s1d and f s2d. The
function f is continuous since it is a polynomial, so the Intermediate Value Theorem
says there is a number c between 1 and 2 such that f scd − 0. In other words, the
equation 4x 3 2 6x 2 1 3x 2 2 − 0 has at least one solution c in the interval s1, 2d.
In fact, we can locate a solution more precisely by using the Intermediate Value
Theorem again. Since
f s1.2d − 20.128 , 0
and
f s1.3d − 0.548 . 0
a solution must lie between 1.2 and 1.3. A calculator gives, by trial and error,
f s1.22d − 20.007008 , 0
and
f s1.23d − 0.056068 . 0
so a solution lies in the interval s1.22, 1.23d.
n
We can use a graphing calculator or computer to illustrate the use of the Intermediate
Value Theorem in Example 10. Figure 10 shows the graph of f in the viewing rectangle
f21, 3g by f23, 3g and you can see that the graph crosses the x-axis between 1 and 2.
Figure 11 shows the result of zooming in to the viewing rectangle f1.2, 1.3g by f20.2, 0.2g.
3
0.2
3
_1
_3
FIGURE 10
1.2
1.3
_0.2
FIGURE 11
In fact, the Intermediate Value Theorem plays a role in the very way these graphing
devices work. A computer calculates a finite number of points on the graph and turns on
the pixels that contain these calculated points. It assumes that the function is continuous
and takes on all the intermediate values between two consecutive points. The computer
therefore “connects the dots” by turning on the intermediate pixels.
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124
CHAPTER 2
Limits and Derivatives
Exercises
2.5
1. Write an equation that expresses the fact that a function f is
continuous at the number 4.
9. Discontinuities at 0 and 3, but continuous from the right at 0
and from the left at 3
2. If f is continuous on s2`, `d, what can you say about its
graph?
10. Continuous only from the left at 21, not continuous from the
left or right at 3
3. (a) From the given graph of f , state the numbers at which f
is discontinuous and explain why.
(b) For each of the numbers stated in part (a), determine
whether f is continuous from the right, or from the left,
or neither.
y
_4
_2
0
2
4
12. Explain why each function is continuous or discontinuous.
(a) The temperature at a specific location as a function of
time
(b) The temperature at a specific time as a function of the
distance due west from New York City
(c) The altitude above sea level as a function of the distance
due west from New York City
(d) The cost of a taxi ride as a function of the distance
traveled
(e) The current in the circuit for the lights in a room as a
function of time
x
6
11. The toll T charged for driving on a certain stretch of a toll
road is $5 except during rush hours (between 7 am and 10 am
and between 4 pm and 7 pm) when the toll is $7.
(a) Sketch a graph of T as a function of the time t, measured
in hours past midnight.
(b) Discuss the discontinuities of this function and their
significance to someone who uses the road.
4. From the given graph of t, state the numbers at which t is
discontinuous and explain why.
y
13–16 Use the definition of continuity and the properties of limits
to show that the function is continuous at the given number a.
13. f sxd − 3x 2 1 sx 1 2d5, a − 21
_3
_2
0
1
2
3
x
14. tstd −
t 2 1 5t
, a−2
2t 1 1
15. psvd − 2s3v 2 1 1 ,
5– 6 The graph of a function f is given.
(a) At what numbers a does lim x l a f sxd not exist?
(b) At what numbers a is f not continuous?
(c) At what numbers a does lim x l a f sxd exist but f is not
continuous at a ?
5.
6.
y
1
x
17. f sxd − x 1 sx 2 4 ,
y
0
1
7 – 10 Sketch the graph of a function f that is defined on R and
continuous except for the stated discontinuities.
7. Removable discontinuity at 22, infinite discontinuity at 2
8. Jump discontinuity at 23, removable discontinuity at 4
2
a − 22
17 –18 Use the definition of continuity and the properties of limits
to show that the function is continuous on the given interval.
18. tsxd −
0
a−1
16. f srd − s4r 2 2r 1 7 ,
3
x
x21
,
3x 1 6
f4, `d
s2`, 22d
19– 24 Explain why the function is discontinuous at the given
number a. Sketch the graph of the function.
19. f sxd −
20. f sxd −
1
x12
H
1
x12
1
a − 22
if x ± 22
a − 22
if x − 22
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SECTION 2.5
21. f sxd −
H
H
H
H
x 1 3 if x < 21
2x
if x . 21
x2 2 x
22. f sxd − x 2 2 1
1
a − 21
a−1
if x − 1
cos x
if x , 0
23. f sxd − 0
if x − 0
1 2 x 2 if x . 0
2x 2 2 5x 2 3
24. f sxd −
x23
6
a−0
if x ± 3
a−3
if x − 3
25 –26
(a) Show that f has a removable discontinuity at x − 3.
(b) Redefine f s3d so that f is continuous at x − 3 (and thus the
discontinuity is “removed”).
25. f sxd −
x23
x2 2 9
2
x 2 7x 1 12
x23
26. f sxd −
27 – 34 Explain, using Theorems 4, 5, 7, and 9, why the
function is continuous at every number in its domain. State
the domain.
27. f sxd −
x2
28. tsvd −
sx 1 2
4
3v 2 1
v 1 2v 2 15
2
cosst 2d
29. hstd −
1 2 et
2
31. Lsvd − v lns1 2 v 2 d
32. f std − e2t lns1 1 t 2 d
1
x
34. tstd − cos21se t 2 1d
Î
11
x l2
S D
37. lim ln
x l1
5 2 x2
11x
36.
1
s1 2 sin x
sin x if x , !y4
cos x if x > !y4
43– 45 Find the numbers at which f is discontinuous. At which
of these numbers is f continuous from the right, from the left,
or neither? Sketch the graph of f .
H
H
H
x 2 if x , 21
43. f sxd − x
if 21 < x , 1
1yx if x > 1
2x
if x < 1
44. f sxd − 3 2 x if 1 , x < 4
if x . 4
sx
x 1 2 if x , 0
45. f sxd − e x
if 0 < x < 1
2 2 x if x . 1
46. The gravitational force exerted by the planet Earth on a unit
mass at a distance r from the center of the planet is
Fsrd −
GMr
R3
GM
r2
if r , R
if r > R
47. For what value of the constant c is the function f continuous on s2`, `d?
f sxd −
lim sinstanscos "dd
" l !y2
38. lim 3 sx 22x24
2
xl4
; 39 –40 Locate the discontinuities of the function and illustrate
by graphing.
39. f sxd −
1 2 x 2 if x < 1
ln x
if x . 1
H
cx 2 1 2x if x , 2
x 3 2 cx
if x > 2
48. Find the values of a and b that make f continuous
everywhere.
35 – 38 Use continuity to evaluate the limit.
35. lim x s20 2 x 2
42. f sxd −
H
H
where M is the mass of Earth, R is its radius, and G is the
gravitational constant. Is F a continuous function of r ?
3
30. Bsud − s3u 2 2 1 s
2u 2 3
33. Msxd −
125
41 – 42 Show that f is continuous on s2`, `d.
41. f sxd −
if x ± 1
Continuity
40. y − arctan
1
x
f sxd −
x2 2 4
if x , 2
x22
2
ax 2 bx 1 3 if 2 < x , 3
2x 2 a 1 b
if x > 3
49. Suppose f and t are continuous functions such that ts2d − 6
and lim x l 2 f3 f sxd 1 f sxd tsxdg − 36. Find f s2d.
50. Let f sxd − 1yx and tsxd − 1yx 2.
(a) Find s f + tds xd.
(b) Is f + t continuous everywhere? Explain.
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126
CHAPTER 2
Limits and Derivatives
51. Which of the following functions f has a removable discontinuity at a? If the discontinuity is removable, find a function t that agrees with f for x ± a and is continuous at a.
(a) f sxd −
x4 2 1
, a−1
x21
(b) f sxd −
x 3 2 x 2 2 2x
, a−2
x22
(c) f sxd − v sin x b , a − !
52. Suppose that a function f is continuous on [0, 1] except at
0.25 and that f s0d − 1 and f s1d − 3. Let N − 2. Sketch
two possible graphs of f , one showing that f might not satisfy the conclusion of the Intermediate Value Theorem and
one showing that f might still satisfy the conclusion of the
Intermediate Value Theorem (even though it doesn’t satisfy
the hypothesis).
66. To prove that sine is continuous, we need to show that
lim x l a sin x − sin a for every real number a. By Exercise 65 an equivalent statement is that
lim sinsa 1 hd − sin a
hl0
Use (6) to show that this is true.
67. Prove that cosine is a continuous function.
68. (a) Prove Theorem 4, part 3.
(b) Prove Theorem 4, part 5.
69. Use Theorem 8 to prove Limit Laws 6 and 7 from
Section 2.3.
70. Is there a number that is exactly 1 more than its cube?
71. For what values of x is f continuous?
H
0 if x is rational
1 if x is irrational
53. If f sxd − x 2 1 10 sin x, show that there is a number c such
that f scd − 1000.
f sxd −
54. Suppose f is continuous on f1, 5g and the only solutions of
the equation f sxd − 6 are x − 1 and x − 4. If f s2d − 8,
explain why f s3d . 6.
72. For what values of x is t continuous?
55– 58 Use the Intermediate Value Theorem to show that there
is a solution of the given equation in the specified interval.
55. 2x 1 4x 1 1 − 0, s21, 0d
tsxd −
57. e x − 3 2 2x,
s2, 3d
s0, 1d
58. sin x − x 2 2 x, s1, 2d
59 – 60
(a) Prove that the equation has at least one real solution.
(b) Use a calculator to find an interval of length 0.01 that
contains a solution.
59. cos x − x 3
60. ln x − 3 2 2x
; 61– 62
(a) Prove that the equation has at least one real solution.
(b) Find the solution correct to three decimal places, by
graphing.
61. 100e2xy100 − 0.01x 2
62. arctan x − 1 2 x
63– 64 Prove, without graphing, that the graph of the function
has at least two x-intercepts in the specified interval.
63. y − sin x 3,
s1, 2d
64. y − x 2 2 3 1 1yx, s0, 2d
65. Prove that f is continuous at a if and only if
lim f sa 1 hd − f sad
hl0
0 if x is rational
x if x is irrational
73. Show that the function
3
56. ln x − x 2 sx ,
H
f sxd −
H
x 4 sins1yxd
0
if x ± 0
if x − 0
is continuous on s2`, `d.
74. If a and b are positive numbers, prove that the equation
a
b
1 3
−0
x 3 1 2x 2 2 1
x 1x22
has at least one solution in the interval s21, 1d.
75. A Tibetan monk leaves the monastery at 7:00 am and
takes his usual path to the top of the mountain, arriving at
7:00 pm. The following morning, he starts at 7:00 am at the
top and takes the same path back, arriving at the monastery
at 7:00 pm. Use the Intermediate Value Theorem to show
that there is a point on the path that the monk will cross at
exactly the same time of day on both days.
76. Absolute Value and Continuity
(a) Show that the absolute value function Fsxd − x is
continuous everywhere.
(b) Prove that if f is a continuous function on an interval,
then so is f .
(c) Is the converse of the statement in part (b) also true?
In other words, if f is continuous, does it follow
that f is continuous? If so, prove it. If not, find a
counterexample.
| |
| |
| |
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SECTION 2.6
127
Limits at Infinity; Horizontal Asymptotes
2.6 Limits at Infinity; Horizontal Asymptotes
In Sections 2.2 and 2.4 we investigated infinite limits and vertical asymptotes of a curve
y − f sxd. There we let x approach a number and the result was that the values of y
became arbitrarily large (positive or negative). In this section we let x become arbitrarily
large ( positive or negative) and see what happens to y.
■ Limits at Infinity and Horizontal Asymptotes
Let’s begin by investigating the behavior of the function f defined by
x
f sxd
0
61
62
63
64
65
610
650
6100
61000
21
0
0.600000
0.800000
0.882353
0.923077
0.980198
0.999200
0.999800
0.999998
f sxd −
x2 2 1
x2 1 1
as x becomes large. The table at the left gives values of this function correct to six decimal places, and the graph of f has been drawn by a computer in Figure 1.
y
y=1
0
1
y=
FIGURE 1
≈-1
≈+1
x
You can see that as x grows larger and larger, the values of f sxd get closer and closer
to 1. (The graph of f approaches the horizontal line y − 1 as we look to the right.) In
fact, it seems that we can make the values of f sxd as close as we like to 1 by taking x
sufficiently large. This situation is expressed symbolically by writing
x2 2 1
−1
xl` x2 1 1
lim
In general, we use the notation
lim f sxd − L
xl`
to indicate that the values of f sxd approach L as x becomes larger and larger.
1 Intuitive Definition of a Limit at Infinity Let f be a function defined on
some interval sa, `d. Then
lim f sxd − L
xl`
means that the values of f sxd can be made arbitrarily close to L by requiring x to
be sufficiently large.
Another notation for lim x l ` f sxd − L is
f sxd l L
as
xl`
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128
CHAPTER 2
Limits and Derivatives
The symbol ` does not represent a number. Nonetheless, the expression lim f sxd − L is
x l`
often read as
“the limit of f sxd, as x approaches infinity, is L”
or
“the limit of f sxd, as x becomes infinite, is L”
or
“the limit of f sxd, as x increases without bound, is L”
The meaning of such phrases is given by Definition 1. A more precise definition, similar
to the «, # definition of Section 2.4, is given at the end of this section.
Geometric illustrations of Definition 1 are shown in Figure 2. Notice that there are
many ways for the graph of f to approach the line y − L (which is called a horizontal
asymptote) as we look to the far right of each graph.
y
y
y=L
y
y=ƒ
y=ƒ
0
y=L
y=ƒ
y=L
x
0
0
x
x
FIGURE 2 Examples illustrating lim f sxd − L
xl`
Referring back to Figure 1, we see that for numerically large negative values of x, the
values of f sxd are close to 1. By letting x decrease through negative values without
bound, we can make f sxd as close to 1 as we like. This is expressed by writing
x2 2 1
−1
x l2` x 2 1 1
lim
The general definition is as follows.
y
2 Definition Let f be a function defined on some interval s2`, ad. Then
y=ƒ
lim f sxd − L
x l 2`
means that the values of f sxd can be made arbitrarily close to L by requiring x to
be sufficiently large negative.
y=L
0
x
y
“the limit of f sxd, as x approaches negative infinity, is L”
Definition 2 is illustrated in Figure 3. Notice that the graph approaches the line y − L as
we look to the far left of each graph.
y=ƒ
y=L
Again, the symbol 2` does not represent a number, but the expression lim f sxd − L
x l 2`
is often read as
0
x
FIGURE 3
Examples illustrating lim f sxd − L
3 Definition The line y − L is called a horizontal asymptote of the curve
y − f sxd if either
lim f sxd − L
or
lim f sxd − L
x l`
x l 2`
x l 2`
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SECTION 2.6
y
Limits at Infinity; Horizontal Asymptotes
129
For instance, the curve illustrated in Figure 1 has the line y − 1 as a horizontal asymptote because
x2 2 1
lim 2
−1
xl` x 1 1
π
2
0
x
An example of a curve with two horizontal asymptotes is y − tan21x. (See Figure 4.)
In fact,
_ π2
4
lim tan21 x − 2
x l2`
!
2
lim tan21 x −
xl`
!
2
FIGURE 4
y − tan21x
so both of the lines y − 2!y2 and y − !y2 are horizontal asymptotes. (This follows
from the fact that the lines x − 6!y2 are vertical asymptotes of the graph of the tangent
function.)
y
EXAMPLE 1 Find the infinite limits, limits at infinity, and asymptotes for the function
f whose graph is shown in Figure 5.
SOLUTION We see that the values of f sxd become large as x l 21 from both sides, so
2
lim f sxd − `
x l21
0
x
2
Notice that f sxd becomes large negative as x approaches 2 from the left, but large
positive as x approaches 2 from the right. So
lim f sxd − 2`
and
x l 22
lim f sxd − `
x l 21
Thus both of the lines x − 21 and x − 2 are vertical asymptotes.
As x becomes large, it appears that f sxd approaches 4. But as x decreases through
negative values, f sxd approaches 2. So
FIGURE 5
lim f sxd − 4
lim f sxd − 2
and
xl`
x l2`
This means that both y − 4 and y − 2 are horizontal asymptotes.
EXAMPLE 2 Find lim
1
xl` x
and lim
1
x l2` x
n
.
SOLUTION Observe that when x is large, 1yx is small. For instance,
y
1
− 0.01
100
y=∆
0
lim
1
1
− 0.000001
1,000,000
In fact, by taking x large enough, we can make 1yx as close to 0 as we please. Therefore, according to Definition 1, we have
x
lim
1
xl` x
−0
Similar reasoning shows that when x is large negative, 1yx is small negative, so we also
have
1
lim
−0
x l2` x
FIGURE 6
xl` x
1
− 0.0001
10,000
− 0, lim
1
x l2` x
−0
It follows that the line y − 0 (the x-axis) is a horizontal asymptote of the curve
y − 1yx. (This is a hyperbola; see Figure 6.)
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n
130
CHAPTER 2
Limits and Derivatives
■ Evaluating Limits at Infinity
Most of the Limit Laws that were given in Section 2.3 also hold for limits at infinity. It
can be proved that the Limit Laws listed in Section 2.3 (with the exception of Laws 10 and
11) are also valid if “x l a” is replaced by “x l `” or “x l 2`.” In particular, if we
combine Laws 6 and 7 with the results of Example 2, we obtain the following important
rule for calculating limits.
5 Theorem If r . 0 is a rational number, then
lim
1
xl` xr
−0
If r . 0 is a rational number such that x r is defined for all x, then
lim
1
x l2` x r
−0
EXAMPLE 3 Evaluate the following limit and indicate which properties of limits are
used at each stage.
3x 2 2 x 2 2
lim
x l ` 5x 2 1 4x 1 1
SOLUTION As x becomes large, both numerator and denominator become large, so it
isn’t obvious what happens to their ratio. We need to do some preliminary algebra.
To evaluate the limit at infinity of any rational function, we first divide both the
numerator and denominator by the highest power of x that occurs in the denominator.
(We may assume that x ± 0, since we are interested only in large values of x.) In this
case the highest power of x in the denominator is x 2, so we have
3x 2 2 x 2 2
1
2
32 2 2
2
2
3x 2 x 2 2
x
x
x
lim
− lim
− lim
x l ` 5x 2 1 4x 1 1
x l ` 5x 2 1 4x 1 1
x l`
4
1
51 1 2
2
x
x
x
S
S
1
2
2 2
x
x
−
4
1
lim 5 1 1 2
xl`
x
x
lim 3 2
xl`
y
y=0.6
0
FIGURE 7
y−
3x 2 2 x 2 2
5x 2 1 4x 1 1
1
x
D
D
1
1
2 2 lim 2
x l`
x l` x
x l` x
−
1
1
lim 5 1 4 lim 1 lim 2
x l`
x l` x
x l` x
(by Limit Law 5)
lim 3 2 lim
−
32020
51010
−
3
5
(by 1, 2, and 3)
(by 8 and Theorem 5)
A similar calculation shows that the limit as x l 2` is also 35. Figure 7 illustrates the
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SECTION 2.6
Limits at Infinity; Horizontal Asymptotes
131
results of these calculations by showing how the graph of the given rational function
approaches the horizontal asymptote y − 35 − 0.6.
n
EXAMPLE 4 Find the horizontal asymptotes of the graph of the function
f sxd −
s2x 2 1 1
3x 2 5
SOLUTION Dividing both numerator and denominator by x (which is the highest power
of x in the denominator) and using the properties of limits, we have
s2x 2 1 1
x
s2x 2 1 1
lim
− lim
− lim
x l ` 3x 2 5
xl`
xl`
3x 2 5
x
lim
−
xl`
lim
y
xl`
Î
Î
S D
32
(since sx 2 − x for x . 0)
1
lim 2 1 lim
xl` x2
xl`
−
5
x
2x 2 1 1
x2
3x 2 5
x
1
lim 3 2 5 lim
s2 1 0
s2
−
325?0
3
−
xl` x
xl`
Therefore the line y − s2 y3 is a horizontal asymptote of the graph of f.
In computing the limit as x l 2`, we must remember that for x , 0, we have
sx 2 − x − 2x. So when we divide the numerator by x, for x , 0 we get
œ„
2
| |
y= 3
œ„
2
y=_ 3
Î
s2x 2 1 1
s2x 2 1 1
−
−2
x
2 sx 2
x
Therefore
s2x 2 1 1
lim
− lim
x l2`
x l2`
3x 2 5
FIGURE 8
s 2x 1 1
3x 2 5
2
y−
1
x2
21
Î
Î
21
2
32
1
x2
5
x
Î
2x 2 1 1
−2
x2
21
Î
1
2 1 lim
2
−
x l2` x 2
1
3 2 5 lim
x l2` x
1
x2
−2
s2
3
Thus the line y − 2s2 y3 is also a horizontal asymptote. See Figure 8.
n
EXAMPLE 5 Compute lim (sx 2 1 1 2 x).
x l`
We can think of the given function as
having a denominator of 1.
SOLUTION Because both sx 2 1 1 and x are large when x is large, it’s difficult to see
what happens to their difference, so we use algebra to rewrite the function. We first
multiply numerator and denominator by the conjugate radical:
lim (sx 2 1 1 2 x) − lim (sx 2 1 1 2 x) !
x l`
y
y=œ„„„„„-x
≈+1
1
0
FIGURE 9
1
x
sx 2 1 1 1 x
sx 2 1 1 1 x
sx 2 1 1d 2 x 2
1
− lim
− lim
x l ` sx 2 1 1 1 x
x l ` sx 2 1 1 1 x
x l`
Notice that the denominator of this last expression (sx 2 1 1 1 x) becomes large as
x l ` (it’s bigger than x). So
1
lim (sx 2 1 1 2 x) − lim
−0
x l`
x l ` sx 2 1 1 1 x
Figure 9 illustrates this result.
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n
132
CHAPTER 2
Limits and Derivatives
S D
1
.
x22
EXAMPLE 6 Evaluate lim1 arctan
x l2
SOLUTION If we let t − 1ysx 2 2d, we know that t l ` as x l 2 1. Therefore, by the
second equation in (4), we have
S D
lim arctan
x l 21
1
x22
− lim arctan t −
tl`
!
2
n
The graph of the natural exponential function y − e x has the line y − 0 (the
x-axis) as a horizontal asymptote. (The same is true of any exponential function with
base b . 1.) In fact, from the graph in Figure 10 and the corresponding table of values, we see that
lim e x − 0
6
x l 2`
Notice that the values of e x approach 0 very rapidly.
y
y=´
1
0
FIGURE 10
x
1
x
ex
0
21
22
23
25
28
210
1.00000
0.36788
0.13534
0.04979
0.00674
0.00034
0.00005
EXAMPLE 7 Evaluate lim2 e 1yx.
x l0
PS The problem-solving strategy for
Examples 6 and 7 is introducing something
extra (see Principles of Problem Solving
following Chapter 1). Here, the something
extra, the auxiliary aid, is the new variable t.
SOLUTION If we let t − 1yx, we know that t l 2` as x l 02. Therefore, by (6),
lim e 1yx − lim e t − 0
x l 02
t l 2`
(See Exercise 81.)
n
EXAMPLE 8 Evaluate lim sin x.
xl`
SOLUTION As x increases, the values of sin x oscillate between 1 and 21 infinitely often
and so they don’t approach any definite number. Thus lim x l` sin x does not exist.
n
■ Infinite Limits at Infinity
The notation
lim f sxd − `
x l`
is used to indicate that the values of f sxd become large as x becomes large. Similar meanings are attached to the following symbols:
lim f sxd − `
x l 2`
lim f sxd − 2`
x l`
lim f sxd − 2`
x l 2`
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 2.6
Limits at Infinity; Horizontal Asymptotes
133
EXAMPLE 9 Find lim x 3 and lim x 3.
xl`
x l2`
SOLUTION When x becomes large, x 3 also becomes large. For instance,
10 3 − 1000
y
1000 3 − 1,000,000,000
In fact, we can make x 3 as big as we like by requiring x to be large enough. Therefore
we can write
y=˛
0
100 3 − 1,000,000
lim x 3 − `
xl`
x
Similarly, when x is large negative, so is x 3. Thus
lim x 3 − 2`
x l2`
FIGURE 11
lim x 3 − `, lim x 3 − 2`
xl`
These limit statements can also be seen from the graph of y − x 3 in Figure 11.
x l2`
n
Looking at Figure 10 we see that
y
y=´
lim e x − `
x l`
but, as Figure 12 demonstrates, y − e x becomes large as x l ` at a much faster rate
than y − x 3.
y=˛
100
0
EXAMPLE 10 Find lim sx 2 2 xd.
x l`
x
1
SOLUTION Limit Law 2 says that the limit of a difference is the difference of the
limits, provided that these limits exist. We cannot use Law 2 here because
FIGURE 12
x
lim x 2 − `
x l`
3
e is much larger than x when
x is large.
and
lim x − `
x l`
In general, the Limit Laws can’t be applied to infinite limits because ` is not a number
(` 2 ` can’t be defined). However, we can write
lim sx 2 2 xd − lim xsx 2 1d − `
x l`
x l`
because both x and x 2 1 become arbitrarily large and so their product does too.
n
x2 1 x
.
xl` 3 2 x
EXAMPLE 11 Find lim
SOLUTION As in Example 3, we divide the numerator and denominator by the highest
power of x in the denominator, which is simply x:
x2 1 x
x11
− lim
− 2`
x l` 3 2 x
x l` 3
21
x
lim
because x 1 1 l ` and 3yx 2 1 l 0 2 1 − 21 as x l `.
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n
134
CHAPTER 2
Limits and Derivatives
The next example shows that by using infinite limits at infinity, together with intercepts, we can get a rough idea of the graph of a polynomial without having to plot a large
number of points.
EXAMPLE 12 Sketch the graph of y − sx 2 2d4sx 1 1d3sx 2 1d by finding its
intercepts and its limits as x l ` and as x l 2`.
SOLUTION The y-intercept is f s0d − s22d4s1d3s21d − 216 and the x-intercepts are
found by setting y − 0: x − 2, 21, 1. Notice that since sx 2 2d4 is never negative, the
function doesn’t change sign at 2; thus the graph doesn’t cross the x-axis at 2. The
graph crosses the axis at 21 and 1.
When x is large positive, all three factors are large, so
y
0
_1
1
2
x
lim sx 2 2d4sx 1 1d3sx 2 1d − `
xl`
When x is large negative, the first factor is large positive and the second and third
factors are both large negative, so
_16
lim sx 2 2d4sx 1 1d3sx 2 1d − `
x l2`
FIGURE 13
y − sx 2 2d4 sx 1 1d3 sx 2 1d
Combining this information, we give a rough sketch of the graph in Figure 13.
n
■ Precise Definitions
Definition 1 can be stated precisely as follows.
7 Precise Definition of a Limit at Infinity Let f be a function defined on
some interval sa, `d. Then
lim f sxd − L
xl`
means that for every « . 0 there is a corresponding number N such that
if
x.N
then
| f sxd 2 L | , «
In words, this says that the values of f sxd can be made arbitrarily close to L (within a
distance «, where « is any positive number) by requiring x to be sufficiently large (larger
than N, where N depends on «). Graphically, it says that by keeping x large enough
(larger than some number N) we can make the graph of f lie between the given horizontal lines y − L 2 « and y − L 1 « as in Figure 14. This must be true no matter how
small we choose «.
y
y=L+∑
∑
L ∑
y=L-∑
FIGURE 14
lim f sxd − L
xl`
0
y=ƒ
ƒ is
in here
x
N
when x is in here
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SECTION 2.6
135
Limits at Infinity; Horizontal Asymptotes
Figure 15 shows that if a smaller value of « is chosen, then a larger value of N may
be required.
y
y=ƒ
y=L+∑
L
y=L-∑
0
FIGURE 15
N
x
lim f sxd − L
xl`
Similarly, a precise version of Definition 2 is given by Definition 8, which is illustrated in Figure 16.
8 Definition Let f be a function defined on some interval s2`, ad. Then
lim f sxd − L
x l 2`
means that for every « . 0 there is a corresponding number N such that
if
x,N
then
| f sxd 2 L | , «
y
y=ƒ
y=L+∑
L
y=L-∑
FIGURE 16
0
N
lim f sxd − L
x
x l2`
In Example 3 we calculated that
3x 2 2 x 2 2
3
−
2
x l ` 5x 1 4x 1 1
5
lim
In the next example we use a calculator (or computer) to relate this statement to Definition 7 with L − 35 − 0.6 and « − 0.1.
EXAMPLE 13 Use a graph to find a number N such that
if
x.N
then
Z
3x 2 2 x 2 2
2 0.6
5x 2 1 4x 1 1
Z
, 0.1
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136
CHAPTER 2
Limits and Derivatives
SOLUTION We rewrite the given inequality as
3x 2 2 x 2 2
, 0.7
5x 2 1 4x 1 1
0.5 ,
1
We need to determine the values of x for which the given curve lies between the horizontal lines y − 0.5 and y − 0.7. So we graph the curve and these lines in Figure 17. Then
we use the graph to estimate that the curve crosses the line y − 0.5 when x < 6.7. To the
right of this number it seems that the curve stays between the lines y − 0.5 and y − 0.7.
Rounding up to be safe, we can say that
y=0.7
y=0.5
y=
3≈-x-2
5≈+4x+1
15
0
FIGURE 17
if
Z
then
x.7
3x 2 2 x 2 2
2 0.6
5x 2 1 4x 1 1
Z
, 0.1
In other words, for « − 0.1 we can choose N − 7 (or any larger number) in Definition 7.
1
EXAMPLE 14 Use Definition 7 to prove that lim
xl` x
− 0.
SOLUTION Given « . 0, we want to find N such that
if
Z
then
x.N
n
1
20
x
Z
,«
In computing the limit we may assume that x . 0. Then 1yx , « &? x . 1y«. Let’s
choose N − 1y«. So
if
x.N−
1
«
Z
then
1
20
x
Z
−
1
,«
x
Therefore, by Definition 7,
lim
1
xl` x
−0
Figure 18 illustrates the proof by showing some values of « and the corresponding
values of N.
y
y
∑=1
0
FIGURE 18
N=1
x
∑=0.2
0
y
N=5
x
∑=0.1
0
N=10
x
n
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SECTION 2.6
y
M
137
Limits at Infinity; Horizontal Asymptotes
Finally we note that an infinite limit at infinity can be defined as follows. The geometric illustration is given in Figure 19.
y=M
9 Precise Definition of an Infinite Limit at Infinity Let f be a function
defined on some interval sa, `d. Then
0
x
N
lim f sxd − `
xl`
FIGURE 19
means that for every positive number M there is a corresponding positive number
N such that
lim f sxd − `
xl`
if
x.N
f sxd . M
then
Similar definitions apply when the symbol ` is replaced by 2`. (See Exercise 80.)
2.6 Exercises
y
1. Explain in your own words the meaning of each of the
following.
(a) lim f sxd − 5
(b) lim f sxd − 3
xl`
x l 2`
1
2. (a) Can the graph of y − f sxd intersect a vertical asymptote?
Can it intersect a horizontal asymptote? Illustrate by
sketching graphs.
(b) How many horizontal asymptotes can the graph of
y − f sxd have? Sketch graphs to illustrate the possibilities.
3. For the function f whose graph is given, state the following.
(a) lim f sxd
(b) lim f sxd
x l`
x l 2`
(c) lim f sxd
(d) lim f sxd
x l1
5–10 Sketch the graph of an example of a function f that satisfies
all of the given conditions.
5. f s2d − 4,
x l3
(e) The equations of the asymptotes
6. f s0d − 0,
y
f s22d − 24,
lim f sxd − `,
x l 12
lim f sxd − 22,
7. lim f sxd − `,
x l0
1
x
x l`
lim f sxd − 21
x l 2`
4. For the function t whose graph is given, state the following.
(a) lim tsxd
(b) lim tsxd
x l`
x l 2`
(c) lim tsxd
(d) lim2 tsxd
(e) lim1 tsxd
(f) The equations of the asymptotes
xl0
x l2
xl2
9. f s0d − 0,
lim f sxd − `
lim f sxd − 2`,
lim f sxd − 1,
lim f sxd − 2`,
x l 221
x l`
10. lim f sxd − 21,
x l 32
lim f sxd − `,
x l 222
x l1
x l 2`
lim f sxd − `,
x l 31
x l`
8. lim f sxd − 2`,
lim f sxd − `,
lim f sxd − 2`,
lim f sxd − 2`,
lim f sxd − 1,
lim f sxd − 2
x l`
x l 11
x l 32
x l 2`
x l2
lim f sxd − 0,
x l 2`
lim f sxd − 22
x l 2`
1
x
1
lim f sxd − 2`,
x l`
lim f sxd − `,
x l 02
f s3d − 4,
lim f sxd − 2`,
x l 01
lim f sxd − 4,
x l 31
f is odd
lim f sxd − 1
x l`
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138
CHAPTER 2
Limits and Derivatives
; 11. Guess the value of the limit
x2
x l` 2x
lim
39.
by evaluating the function f sxd − x 2y2 x for x − 0, 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 20, 50, and 100. Then use a graph of f to
support your guess.
S D
f sxd − 1 2
2
x
2
2x 2 7
5x 2 1 x 2 3
14. lim
xl`
Î
3
9x 1 8x 2 4
3 2 5x 1 x 3
15–42 Find the limit or show that it does not exist.
4x 1 3
x l ` 5x 2 1
22
16. lim
x l ` 3x 1 7
2
3t 1 t
17. lim
t l 2` t 3 2 4t 1 1
r 2 r3
19. lim
r l ` 2 2 r 2 1 3r 3
21. lim
4 2 sx
x l ` 2 1 sx
sx 1 3x 2
23. lim
xl`
4x 2 1
18.
lim
t l 2`
6t 1 t 2 5
9 2 2t 2
3x 3 2 8x 1 2
20. lim
x l ` 4x 3 2 5x 2 2 2
22.
su 2 1 1ds2u 2 2 1d
u l 2`
su 2 1 2d2
lim
24. lim
tl`
26.
27. lim
2x 5 2 x
x l 2` x 4 1 3
28. lim
29. lim (s25t 2 1 2 2 5t)
30.
t13
s2t 2 2 1
s1 1 4x 6
x l 2`
2 2 x3
lim
q 3 1 6q 2 4
q l ` 4q 2 2 3q 1 3
lim (s4x 2 1 3x 1 2 x )
x l2`
31. lim (sx 2 1 ax 2 sx 2 1 bx )
x l`
32. lim ( x 2 sx )
xl`
33. lim sx 2 1 2x 7 d
34. lim se2x 1 2 cos 3xd
35. lim se22x cos xd
sin2 x
36. lim 2
xl` x 1 1
x l 2`
xl`
41. lim flns1 1 x d 2 lns1 1 xdg
xl `
42. lim flns2 1 xd 2 lns1 1 xdg
x
find each of the following limits.
ln x
(i) lim1 f sxd
xl0
(ii) lim2 f sxd
(iii) lim1 f sxd
xl1
x l1
(b) Use a table of values to estimate lim f sxd.
xl`
(c) Use the information from parts (a) and (b) to make a
rough sketch of the graph of f.
44. (a) For f sxd −
2
1
2
find each of the following limits.
x
ln x
(i) lim f sxd
xl`
(ii) lim1 f sxd
(iii) lim2 f sxd
(iv) lim1 f sxd
xl1
xl0
x l1
(b) Use the information from part (a) to make a rough
sketch of the graph of f.
; 45. (a) Estimate the value of
lim (sx 2 1 x 1 1 1 x)
2
s1 1 4x 6
xl`
2 2 x3
25. lim
tl`
xl0
2
43. (a) For f sxd −
13–14 Evaluate the limit and justify each step by indicating the
appropriate properties of limits.
15. lim
40. lim1 tan21sln xd
e sec x
x
to estimate the value of lim x l ` f sxd correct to two
decimal places.
(b) Use a table of values of f sxd to estimate the limit to
four decimal places.
xl`
lim
x ls!y2d1
38. lim
xl `
; 12. (a) Use a graph of
13. lim
e 3x 2 e23x
x l ` e 3x 1 e23x
1 2 ex
x l ` 1 1 2e x
37. lim
x l 2`
by graphing the function f sxd − sx 2 1 x 1 1 1 x.
(b) Use a table of values of f sxd to guess the value of the
limit.
(c) Prove that your guess is correct.
; 46. (a) Use a graph of
f sxd − s3x 2 1 8x 1 6 2 s3x 2 1 3x 1 1
to estimate the value of lim x l ` f sxd to one decimal
place.
(b) Use a table of values of f sxd to estimate the limit to
four decimal places.
(c) Find the exact value of the limit.
47–52 Find the horizontal and vertical asymptotes of each
curve. You may want to use a graphing calculator (or computer)
to check your work by graphing the curve and estimating the
asymptotes.
47. y −
5 1 4x
x13
48. y −
2x 2 1 1
3x 1 2x 2 1
49. y −
2x 2 1 x 2 1
x2 1 x 2 2
50. y −
1 1 x4
x2 2 x4
51. y −
x3 2 x
x 2 6x 1 5
52. y −
2e x
e 25
xl`
2
2
x
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SECTION 2.6
; 53. Estimate the horizontal asymptote of the function
f sxd −
3
60. y − 2x 3 2 x 4
by graphing f for 210 < x < 10. Then calculate the equation of the asymptote by evaluating the limit. How do you
explain the discrepancy?
61. y − x 4 2 x 6
62. y − x 3sx 1 2d 2sx 2 1d
63. y − s3 2 xds1 1 xd 2s1 2 xd 4
; 54. (a) Graph the function
64. y − x 2sx 2 2 1d 2sx 1 2d
f sxd −
s2x 1 1
3x 2 5
2
How many horizontal and vertical asymptotes do you
observe? Use the graph to estimate the values of the
limits
s2x 2 1 1
x l`
3x 2 5
lim
and
s2x 2 1 1
x l 2`
3x 2 5
lim
(b) By calculating values of f sxd, give numerical estimates
of the limits in part (a).
(c) Calculate the exact values of the limits in part (a). Did
you get the same value or different values for these two
limits? [In view of your answer to part (a), you might
have to check your calculation for the second limit.]
lim
xl`
;
; 66. End Behavior of a Function By the end behavior of a
function we mean the behavior of its values as x l ` and
as x l 2`.
(a) Describe and compare the end behavior of the functions
Psxd − 3x 5 2 5x 3 1 2x
Psxd
67. Find lim x l ` f sxd if, for all x . 1,
10e x 2 21
5sx
, f sxd ,
2e x
sx 2 1
if the degree of P is (a) less than the degree of Q and
(b) greater than the degree of Q.
68. (a) A tank contains 5000 L of pure water. Brine that contains 30 g of salt per liter of water is pumped into the
tank at a rate of 25 Lymin. Show that the concentration
of salt after t minutes (in grams per liter) is
56. Make a rough sketch of the curve y − x n (n an integer)
for the following five cases:
(i) n − 0
(ii) n . 0, n odd
(iii) n . 0, n even
(iv) n , 0, n odd
(v) n , 0, n even
Then use these sketches to find the following limits.
(a) lim1 x n
(b) lim2 x n
x l0
Cstd −
x l0
(d)
x l`
(b) What happens to the concentration as t l ` ?
lim x n
lim f sxd − 2`,
x l0
lim2 f sxd − `,
x l 31
69. In Chapter 9 we will be able to show, under certain assumptions, that the velocity vstd of a falling raindrop at time t is
vstd − v *s1 2 e 2ttyv * d
f s2d − 0,
lim f sxd − 2`
58. Find a formula for a function that has vertical asymptotes
x − 1 and x − 3 and horizontal asymptote y − 1.
59. A function f is a ratio of quadratic functions and has a
vertical asymptote x − 4 and just one x-intercept, x − 1.
It is known that f has a removable discontinuity at x − 21
and lim x l21 f sxd − 2. Evaluate
(a) f s0d
(b) lim f sxd
xl`
30t
200 1 t
x l 2`
57. Find a formula for a function f that satisfies the following
conditions:
x l 6`
Qsxd − 3x 5
by graphing both functions in the viewing rectangles
f22, 2g by f22, 2g and f210, 10g by f210,000, 10,000g.
(b) Two functions are said to have the same end behavior if
their ratio approaches 1 as x l `. Show that P and Q
have the same end behavior.
x l ` Qsxd
(c) lim x n
sin x
.
x
(b) Graph f sxd − ssin xdyx. How many times does the
graph cross the asymptote?
65. (a) Use the Squeeze Theorem to evaluate lim
55. Let P and Q be polynomials. Find
x l3
139
60–64 Find the limits as x l ` and as x l 2`. Use this information, together with intercepts, to give a rough sketch of the
graph as in Example 12.
2
3x 1 500x
x 3 1 500x 2 1 100x 1 2000
lim f sxd − 0,
Limits at Infinity; Horizontal Asymptotes
;
where t is the acceleration due to gravity and v * is the
terminal velocity of the raindrop.
(a) Find lim t l ` vstd.
(b) Graph vstd if v* − 1 mys and t − 9.8 mys2. How long
does it take for the velocity of the raindrop to reach
99% of its terminal velocity?
2xy10
and y − 0.1 on a common
; 70. (a) By graphing y − e
screen, discover how large you need to make x so that
e 2xy10 , 0.1.
(b) Can you solve part (a) without using a graph?
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140
CHAPTER 2
Limits and Derivatives
; 71. Use a graph to find a number N such that
if
x.N
Z
then
Z
3x2 1 1
2 1.5 , 0.05
2x 2 1 x 1 1
76. (a) How large do we have to take x so that 1ysx , 0.0001?
(b) Taking r − 12 in Theorem 5, we have the statement
lim
1
x l ` sx
; 72. For the limit
lim
1 2 3x
xl` sx 2 1 1
− 23
illustrate Definition 7 by finding values of N that correspond
to « − 0.1 and « − 0.05.
; 73. For the limit
1 2 3x
lim
x l2` sx 2 1 1
−0
Prove this directly using Definition 7.
77. Use Definition 8 to prove that lim
x l2`
1
− 0.
x
78. Prove, using Definition 9, that lim x 3 − `.
xl`
79. Use Definition 9 to prove that lim e x − `.
xl`
−3
80. Formulate a precise definition of
lim f sxd − 2`
illustrate Definition 8 by finding values of N that correspond
to « − 0.1 and « − 0.05.
x l2`
Then use your definition to prove that
; 74. For the limit
lim s1 1 x 3 d − 2`
lim sx ln x − `
x l2`
xl`
illustrate Definition 9 by finding a value of N that corresponds to M − 100.
75. (a) How large do we have to take x so that
1yx 2 , 0.0001?
(b) Taking r − 2 in Theorem 5, we have the statement
1
lim
−0
xl` x2
81. (a) Prove that
lim f sxd − lim1 f s1ytd
tl0
xl`
f s1ytd
lim f sxd − t lim
l 02
and
xl2`
assuming that these limits exist.
(b) Use part (a) and Exercise 65 to find
lim x sin
Prove this directly using Definition 7.
x l 01
1
x
2.7 Derivatives and Rates of Change
Now that we have defined limits and have learned techniques for computing them, we
revisit the problems of finding tangent lines and velocities from Section 2.1. The special
type of limit that occurs in both of these problems is called a derivative and we will see
that it can be interpreted as a rate of change in any of the natural or social sciences or
engineering.
■ Tangents
If a curve C has equation y − f sxd and we want to find the tangent line to C at the point
Psa, f sadd, then we consider (as we did in Section 2.1) a nearby point Qsx, f sxdd, where
x ± a, and compute the slope of the secant line PQ:
mPQ −
f sxd 2 f sad
x2a
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 2.7
y
P { a, f(a)}
x-a
1 Definition The tangent line to the curve y − f sxd at the point Psa, f sadd is
the line through P with slope
a
y
141
Then we let Q approach P along the curve C by letting x approach a. If mPQ approaches
a number m, then we define the tangent line , to be the line through P with slope m.
(This amounts to saying that the tangent line is the limiting position of the secant line PQ
ƒ-f(a) as Q approaches P. See Figure 1.)
Q{ x, ƒ }
0
Derivatives and Rates of Change
x
x
m − lim
xla
f sxd 2 f sad
x2a
provided that this limit exists.
L
Q
In our first example we confirm the guess we made in Example 2.1.1.
Q
Q
P
EXAMPLE 1 Find an equation of the tangent line to the parabola y − x 2 at the
point Ps1, 1d.
SOLUTION Here we have a − 1 and f sxd − x 2, so the slope is
f sxd 2 f s1d
x2 2 1
− lim
x l1
x l1 x 2 1
x21
x
0
m − lim
FIGURE 1
− lim
x l1
sx 2 1dsx 1 1d
x21
− lim sx 1 1d − 1 1 1 − 2
x l1
Using the point-slope form of the equation of a line, we find that an equation of the
tangent line at s1, 1d is
Point-slope form for a line through
the point sx1 , y1 d with slope m:
y 2 y1 − msx 2 x 1 d
y 2 1 − 2sx 2 1d
or
y − 2x 2 1
n
We sometimes refer to the slope of the tangent line to a curve at a point as the slope
of the curve at the point. The idea is that if we zoom in far enough toward the point,
the curve looks almost like a straight line. Figure 2 illustrates this procedure for the
curve y − x 2 in Example 1. The more we zoom in, the more the parabola looks like a
line. In other words, the curve becomes almost indistinguishable from its tangent line.
2
1.5
(1, 1)
0
1.1
(1, 1)
2
0.5
(1, 1)
1.5
0.9
FIGURE 2
Zooming in toward the point (1, 1) on the parabola y − x 2
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1.1
142
CHAPTER 2
y
L
Limits and Derivatives
Q { a+h, f(a+h)}
There is another expression for the slope of a tangent line that is sometimes easier to
use. If h − x 2 a, then x − a 1 h and so the slope of the secant line PQ is
P { a, f(a)}
mPQ −
f(a+h)-f(a)
h
0
a
a+h
x
FIGURE 3
f sa 1 hd 2 f sad
h
(See Figure 3 where the case h . 0 is illustrated and Q is located to the right of P. If it
happened that h , 0, however, Q would be to the left of P.)
Notice that as x approaches a, h approaches 0 (because h − x 2 a) and so the expression for the slope of the tangent line in Definition 1 becomes
2
m − lim
hl0
f sa 1 hd 2 f sad
h
EXAMPLE 2 Find an equation of the tangent line to the hyperbola y − 3yx at the
point s3, 1d.
SOLUTION Let f sxd − 3yx. Then, by Equation 2, the slope of the tangent at s3, 1d is
f s3 1 hd 2 f s3d
hl0
h
m − lim
3
3 2 s3 1 hd
21
31h
31h
− lim
− lim
hl0
hl0
h
h
y
− lim
3
y=
x
x+3y-6=0
which simplifies to
FIGURE 4
1
1
−2
31h
3
x 1 3y 2 6 − 0
The hyperbola and its tangent are shown in Figure 4.
position at
time t=a
position at
time t=a+h
f(a+h)-f(a)
f(a)
f(a+h)
FIGURE 5
hl0
y 2 1 − 213 sx 2 3d
x
0
− lim 2
Therefore an equation of the tangent at the point s3, 1d is
(3, 1)
0
2h
h l 0 hs3 1 hd
s
n
■ Velocities
In Section 2.1 we investigated the motion of a ball dropped from the CN Tower and
defined its velocity to be the limiting value of average velocities over shorter and shorter
time periods.
In general, suppose an object moves along a straight line according to an equation of
motion s − f std, where s is the displacement (directed distance) of the object from the
origin at time t. The function f that describes the motion is called the position function
of the object. In the time interval from t − a to t − a 1 h , the change in position is
f sa 1 hd 2 f sad. (See Figure 5.)
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SECTION 2.7
s
Q { a+h, f(a+h)}
0
a
average velocity −
mPQ=
a+h
t
f(a+h)-f(a)
h
143
The average velocity over this time interval is
P { a, f(a)}
h
Derivatives and Rates of Change
displacement
f sa 1 hd 2 f sad
−
time
h
which is the same as the slope of the secant line PQ in Figure 6.
Now suppose we compute the average velocities over shorter and shorter time intervals fa, a 1 hg. In other words, we let h approach 0. As in the example of the falling ball,
we define the velocity (or instantaneous velocity) vsad at time t − a to be the limit of
these average velocities.
! average velocity
FIGURE 6
3 Definition The instantaneous velocity of an object with position function
f std at time t − a is
vsad − lim
hl0
f sa 1 hd 2 f sad
h
provided that this limit exists.
This means that the velocity at time t − a is equal to the slope of the tangent line at P
(compare Equation 2 and the expression in Definition 3).
Now that we know how to compute limits, let’s reconsider the problem of the falling ball from Example 2.1.3.
EXAMPLE 3 Suppose that a ball is dropped from the upper observation deck of the
CN Tower, 450 m above the ground.
(a) What is the velocity of the ball after 5 seconds?
(b) How fast is the ball traveling when it hits the ground?
Recall from Section 2.1: The distance
(in meters) fallen after t seconds
is 4.9t 2.
SOLUTION Since two different velocities are requested, it’s efficient to start by finding
the velocity at a general time t − a. Using the equation of motion s − f std − 4.9t 2,
we have
f sa 1 hd 2 f sad
4.9sa 1 hd2 2 4.9a 2
− lim
hl0
hl0
h
h
v sad − lim
4.9sa 2 1 2ah 1 h 2 2 a 2 d
4.9s2ah 1 h 2 d
− lim
hl0
hl0
h
h
− lim
4.9hs2a 1 hd
− lim 4.9s2a 1 hd − 9.8a
hl0
hl0
h
− lim
(a) The velocity after 5 seconds is vs5d − s9.8ds5d − 49 mys.
(b) Since the observation deck is 450 m above the ground, the ball will hit the ground
at the time t when sstd − 450, that is,
4.9t 2 − 450
This gives
t2 −
450
4.9
and
t−
Î
450
< 9.6 s
4.9
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144
CHAPTER 2
Limits and Derivatives
The velocity of the ball as it hits the ground is therefore
v
SÎ D Î
450
4.9
− 9.8
450
< 94 mys
4.9
n
■ Derivatives
We have seen that the same type of limit arises in finding the slope of a tangent line
(Equation 2) or the velocity of an object (Definition 3). In fact, limits of the form
lim
h l0
f sa 1 hd 2 f sad
h
arise whenever we calculate a rate of change in any of the sciences or engineering, such
as a rate of reaction in chemistry or a marginal cost in economics. Since this type of limit
occurs so widely, it is given a special name and notation.
4 Definition The derivative of a function f at a number a, denoted by f 9sad,
is
f 9sad − lim
f 9sad is read “ f prime of a.”
h l0
f sa 1 hd 2 f sad
h
if this limit exists.
If we write x − a 1 h, then we have h − x 2 a and h approaches 0 if and only if x
approaches a. Therefore an equivalent way of stating the definition of the derivative, as
we saw in finding tangent lines (see Definition 1), is
5
f 9sad − lim
xla
f sxd 2 f sad
x2a
EXAMPLE 4 Use Definition 4 to find the derivative of the function f sxd − x 2 2 8x 1 9
at the numbers (a) 2 and (b) a.
Definitions 4 and 5 are equivalent, so
we can use either one to compute the
derivative. In practice, Definition 4
often leads to simpler computations.
SOLUTION
(a) From Definition 4 we have
f 9s2d − lim
h l0
f s2 1 hd 2 f s2d
h
s2 1 hd2 2 8s2 1 hd 1 9 2 s23d
h l0
h
− lim
4 1 4h 1 h 2 2 16 2 8h 1 9 1 3
h l0
h
− lim
h 2 2 4h
hsh 2 4d
− lim
− lim sh 2 4d − 24
h l0
h l0
h l0
h
h
− lim
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SECTION 2.7
(b)
Derivatives and Rates of Change
145
f sa 1 hd 2 f sad
h
f 9sad − lim
h l0
fsa 1 hd2 2 8sa 1 hd 1 9g 2 fa 2 2 8a 1 9g
h l0
h
− lim
a 2 1 2ah 1 h 2 2 8a 2 8h 1 9 2 a 2 1 8a 2 9
h l0
h
− lim
2ah 1 h 2 2 8h
− lim s2a 1 h 2 8d − 2a 2 8
h l0
h l0
h
− lim
As a check on our work in part (a), notice that if we let a − 2, then
f 9s2d − 2s2d 2 8 − 24.
n
EXAMPLE 5 Use Equation 5 to find the derivative of the function f sxd − 1ysx at the
number a sa . 0d.
SOLUTION From Equation 5 we get
f sxd 2 f sad
x2a
f 9sad − lim
xla
1
2
1
1
2
1
sx
sa
sx
sa sx sa
− lim
?
xla
xla
x2a
x2a
sx sa
− lim
sa 2 sx
− lim
− lim
x l a sax sx 2 ad
sa 2 sx
x l a sax sx 2 ad
2sx 2 ad
− lim
(
x l a sax sx 2 ad sa 1 sx
−
21
sa (sa 1 sa )
2
−
)
21
a ? 2 sa
?
− lim
sa 1 sx
sa 1 sx
21
(
x l a sax sa 1 sx
−2
)
1
2a3y2
You can verify that using Definition 4 gives the same result.
n
We defined the tangent line to the curve y − f sxd at the point Psa, f sadd to be the line
that passes through P and has slope m given by Equation 1 or 2. Since, by Definition 4
(and Equation 5), this is the same as the derivative f 9sad, we can now say the following.
The tangent line to y − f sxd at sa, f sadd is the line through sa, f sadd whose slope is
equal to f 9sad, the derivative of f at a.
If we use the point-slope form of the equation of a line, we can write an equation of
the tangent line to the curve y − f sxd at the point sa, f sadd:
y 2 f sad − f 9sadsx 2 ad
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146
CHAPTER 2
Limits and Derivatives
EXAMPLE 6 Find an equation of the tangent line to the parabola y − x 2 2 8x 1 9 at
y
the point s3, 26d.
y=≈-8x+9
x
0
SOLUTION From Example 4(b) we know that the derivative of f sxd − x 2 2 8x 1 9 at
the number a is f 9sad − 2a 2 8. Therefore the slope of the tangent line at s3, 26d is
f 9s3d − 2s3d 2 8 − 22. Thus an equation of the tangent line, shown in Figure 7, is
y 2 s26d − s22dsx 2 3d
(3, _6)
or
y − 22x
n
■ Rates of Change
y=_2 x
Suppose y is a quantity that depends on another quantity x. Thus y is a function of x and
we write y − f sxd. If x changes from x 1 to x 2 , then the change in x (also called the increment of x) is
Dx − x 2 2 x 1
FIGURE 7
and the corresponding change in y is
Dy − f sx 2d 2 f sx 1d
The difference quotient
Dy
f sx 2d 2 f sx 1d
−
Dx
x2 2 x1
is called the average rate of change of y with respect to x over the interval fx 1, x 2g and
can be interpreted as the slope of the secant line PQ in Figure 8.
y
Q { ¤, ‡}
P {⁄, fl}
Îy
Îx
0
⁄
¤
x
average rate of change ! mPQ
FIGURE 8
instantaneous rate of change ! slope of tangent at P
By analogy with velocity, we consider the average rate of change over smaller and
smaller intervals by letting x 2 approach x 1 and therefore letting Dx approach 0. The limit
of these average rates of change is called the (instantaneous) rate of change of y with
respect to x at x − x1, which (as in the case of velocity) is interpreted as the slope of the
tangent to the curve y − f sxd at Psx 1, f sx 1dd:
6
instantaneous rate of change − lim
Dx l 0
Dy
f sx2 d 2 f sx1d
− lim
x
l
x
Dx
x2 2 x1
2
1
We recognize this limit as being the derivative f 9sx 1d.
We know that one interpretation of the derivative f 9sad is as the slope of the tangent
line to the curve y − f sxd when x − a. We now have a second interpretation:
The derivative f 9sad is the instantaneous rate of change of y − f sxd with respect
to x when x − a.
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SECTION 2.7
y
Q
P
x
FIGURE 9
The y-values are changing rapidly
at P and slowly at Q.
Derivatives and Rates of Change
147
The connection with the first interpretation is that if we sketch the curve y − f sxd,
then the instantaneous rate of change is the slope of the tangent to this curve at the point
where x − a. This means that when the derivative is large (and therefore the curve is
steep, as at the point P in Figure 9), the y-values change rapidly. When the derivative is
small, the curve is relatively flat (as at point Q) and the y-values change slowly.
In particular, if s − f std is the position function of a particle that moves along a
straight line, then f 9sad is the rate of change of the displacement s with respect to the
time t. In other words, f 9sad is the velocity of the particle at time t − a. The speed of the
particle is the absolute value of the velocity, that is, f 9sad .
In the next example we discuss the meaning of the derivative of a function that is
defined verbally.
|
|
EXAMPLE 7 A manufacturer produces bolts of a fabric with a fixed width. The cost of
producing x yards of this fabric is C − f sxd dollars.
(a) What is the meaning of the derivative f 9sxd? What are its units?
(b) In practical terms, what does it mean to say that f 9s1000d − 9?
(c) Which do you think is greater, f 9s50d or f 9s500d? What about f 9s5000d?
SOLUTION
(a) The derivative f 9sxd is the instantaneous rate of change of C with respect to x; that
is, f 9sxd means the rate of change of the production cost with respect to the number of
yards produced. (Economists call this rate of change the marginal cost. This idea is
discussed in more detail in Sections 3.7 and 4.7.)
Because
DC
f 9sxd − lim
Dx l 0 Dx
Here we are assuming that the cost
function is well behaved; in other
words, Csxd doesn’t oscillate rapidly
near x − 1000.
the units for f 9sxd are the same as the units for the difference quotient DCyDx. Since
DC is measured in dollars and Dx in yards, it follows that the units for f 9sxd are dollars
per yard.
(b) The statement that f 9s1000d − 9 means that, after 1000 yards of fabric have been
manufactured, the rate at which the production cost is increasing is $9yyard. (When
x − 1000, C is increasing 9 times as fast as x.)
Since Dx − 1 is small compared with x − 1000, we could use the approximation
f 9s1000d <
DC
DC
−
− DC
Dx
1
and say that the cost of manufacturing the 1000th yard (or the 1001st) is about $9.
(c) The rate at which the production cost is increasing (per yard) is probably lower
when x − 500 than when x − 50 (the cost of making the 500th yard is less than the
cost of the 50th yard) because of economies of scale. (The manufacturer makes more
efficient use of the fixed costs of production.) So
f 9s50d . f 9s500d
But, as production expands, the resulting large-scale operation might become inefficient and there might be overtime costs. Thus it is possible that the rate of increase of
costs will eventually start to rise. So it may happen that
f 9s5000d . f 9s500d
n
In the following example we estimate the rate of change of the national debt with
respect to time. Here the function is defined not by a formula but by a table of values.
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148
CHAPTER 2
Limits and Derivatives
t
Dstd
2000
2004
2008
2012
2016
5662.2
7596.1
10,699.8
16,432.7
19,976.8
EXAMPLE 8 Let Dstd be the US national debt at time t. The table in the margin gives
approximate values of this function by providing end of year estimates, in billions of
dollars, from 2000 to 2016. Interpret and estimate the value of D9s2008d.
SOLUTION The derivative D9s2008d means the rate of change of D with respect to t
when t − 2008, that is, the rate of increase of the national debt in 2008.
According to Equation 5,
Dstd 2 Ds2008d
t l 2008
t 2 2008
Source: US Dept. of the Treasury
D9s2008d − lim
One way we can estimate this value is to compare average rates of change over
different time intervals by computing difference quotients, as compiled in the following table.
A Note On Units
The units for the average rate of
change D DyDt are the units for D D
divided by the units for Dt, namely
billions of dollars per year. The instantaneous rate of change is the limit of
the average rates of change, so it is
measured in the same units: billions
of dollars per year.
t
Time interval
Average rate of change −
2000
[2000, 2008]
629.7
2004
[2004, 2008]
775.93
2012
2016
[2008, 2012]
[2008, 2016]
1433.23
1159.63
Dstd 2 Ds2008d
t 2 2008
From this table we see that D9s2008d lies somewhere between 775.93 and 1433.23 billion dollars per year. [Here we are making the reasonable assumption that the debt didn’t
fluctuate wildly between 2004 and 2012.] A good estimate for the rate of increase of the
US national debt in 2008 would be the average of these two numbers, namely
D9s2008d < 1105 billion dollars per year
Another method would be to plot the debt function and estimate the slope of the
tangent line when t − 2008.
n
In Examples 3, 7, and 8 we saw three specific examples of rates of change: the velocity
of an object is the rate of change of displacement with respect to time; marginal cost is the
rate of change of production cost with respect to the number of items produced; the rate
of change of the debt with respect to time is of interest in economics. Here is a small
sample of other rates of change: In physics, the rate of change of work with respect to time
is called power. Chemists who study a chemical reaction are interested in the rate of
change in the concentration of a reactant with respect to time (called the rate of reaction).
A biologist is interested in the rate of change of the population of a colony of bacteria
with respect to time. In fact, the computation of rates of change is important in all of the
natural sciences, in engineering, and even in the social sciences. Further examples will
be given in Section 3.7.
All these rates of change are derivatives and can therefore be interpreted as slopes of
tangents. This gives added significance to the solution of the tangent problem. Whenever
we solve a problem involving tangent lines, we are not just solving a problem in geometry. We are also implicitly solving a great variety of problems involving rates of change
in science and engineering.
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SECTION 2.7
Derivatives and Rates of Change
149
2.7 Exercises
1. A curve has equation y − f sxd.
(a) Write an expression for the slope of the secant line
through the points Ps3, f s3dd and Qsx, f sxdd.
(b) Write an expression for the slope of the tangent line at P.
x
; 2. Graph the curve y − e in the viewing rectangles f21, 1g by
f0, 2g, f20.5, 0.5g by f0.5, 1.5g, and f20.1, 0.1g by
f0.9, 1.1g. What do you notice about the curve as you zoom
in toward the point s0, 1d?
3. (a) Find the slope of the tangent line to the parabola
y − x 2 1 3x at the point s21, 22d
(i) using Definition 1
(ii) using Equation 2
(b) Find an equation of the tangent line in part (a).
(c) Graph the parabola and the tangent line. As a check on
;
your work, zoom in toward the point s21, 22d until the
parabola and the tangent line are indistinguishable.
4. (a) Find the slope of the tangent line to the curve
y − x 3 1 1 at the point s1, 2d
(i) using Definition 1
(ii) using Equation 2
(b) Find an equation of the tangent line in part (a).
(c) Graph the curve and the tangent line in successively
;
smaller viewing rectangles centered at s1, 2d until the
curve and the line appear to coincide.
5–8 Find an equation of the tangent line to the curve at the
given point.
5. y − 2x 2 2 5x 1 1, s3, 4d
6. y − x 2 2 2x 3,
7. y −
x12
,
x23
s1, 21d
s2, 24d
12. If a rock is thrown upward on the planet Mars with a velocity of 10 mys, its height (in meters) after t seconds is given
by H − 10t 2 1.86t 2.
(a) Find the velocity of the rock after one second.
(b) Find the velocity of the rock when t − a.
(c) When will the rock hit the surface?
(d) With what velocity will the rock hit the surface?
13. The displacement (in meters) of a particle moving in a
straight line is given by the equation of motion s − 1yt 2,
where t is measured in seconds. Find the velocity of the
particle at times t − a, t − 1, t − 2, and t − 3.
14. The displacement (in feet) of a particle moving in a straight
line is given by s − 12 t 2 2 6t 1 23, where t is measured in
seconds.
(a) Find the average velocity over each time interval:
(i) f4, 8g
(ii) f6, 8g
(iii) f8, 10g
(iv) f8, 12g
(b) Find the instantaneous velocity when t − 8.
(c) Draw the graph of s as a function of t and draw the
secant lines whose slopes are the average velocities in
part (a). Then draw the tangent line whose slope is the
instantaneous velocity in part (b).
15. (a) A particle starts by moving to the right along a horizontal line; the graph of its position function is shown in
the figure. When is the particle moving to the right?
Moving to the left? Standing still?
(b) Draw a graph of the velocity function.
s (meters)
4
8. y − s1 2 3x , s21, 2d
9. (a) Find the slope of the tangent to the curve
y − 3 1 4x 2 2 2x 3 at the point where x − a.
(b) Find equations of the tangent lines at the points s1, 5d
and s2, 3d.
(c) Graph the curve and both tangents on a common screen.
;
10. (a) Find the slope of the tangent to the curve y − 2sx at
the point where x − a.
(b) Find equations of the tangent lines at the points s1, 2d
and s9, 6d.
(c) Graph the curve and both tangents on a common screen.
;
11. A cliff diver plunges from a height of 100 ft above the water
surface. The distance the diver falls in t seconds is given by
the function dstd − 16t 2 ft.
(a) After how many seconds will the diver hit the water?
(b) With what velocity does the diver hit the water?
2
0
2
4
6 t (seconds)
16. Shown are graphs of the position functions of two runners,
A and B, who run a 100-meter race and finish in a tie.
(a) Describe and compare how the runners run the race.
(b) At what time is the distance between the runners the
greatest?
(c) At what time do they have the same velocity?
s (meters)
80
A
40
0
B
4
8
12
t (seconds)
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
150
CHAPTER 2
Limits and Derivatives
17. For the function t whose graph is given, arrange the following numbers in increasing order and explain your reasoning:
t9s22d
0
t9s0d
t9s2d
y
t9s4d
30. If tsxd − x 4 2 2, find t9s1d and use it to find an equation of
the tangent line to the curve y − x 4 2 2 at the point s1, 21d.
y=©
_1 0
1
2
3
31. (a) If Fsxd − 5xys1 1 x 2 d, find F9s2d and use it to find an
equation of the tangent line to the curve y − 5xys1 1 x 2 d
at the point s2, 2d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on the same screen.
x
4
18. The graph of a function f is shown.
(a) Find the average rate of change of f on the interval f20, 60g.
(b) Identify an interval on which the average rate of change
of f is 0.
(c) Compute
f s40d 2 f s10d
40 2 10
32. (a) If Gsxd − 4x 2 2 x 3, find G9sad and use it to find equations of the tangent lines to the curve y − 4x 2 2 x 3 at
the points s2, 8d and s3, 9d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
lines on the same screen.
33. If an equation of the tangent line to the curve y − f sxd at the
point where a − 2 is y − 4x 2 5, find f s2d and f 9s2d.
34. If the tangent line to y − f sxd at (4, 3) passes through the
point (0, 2), find f s4d and f 9s4d.
What does this value represent geometrically?
(d) Estimate the value of f 9s50d.
(e) Is f 9s10d . f 9s30d?
(f ) Is f 9s60d .
29. If f sxd − 3x 2 2 x 3, find f 9s1d and use it to find an equation of
the tangent line to the curve y − 3x 2 2 x 3 at the point s1, 2d.
35–36 A particle moves along a straight line with equation of
motion s − f std, where s is measured in meters and t in seconds.
Find the velocity and the speed when t − 4.
f s80d 2 f s40d
? Explain.
80 2 40
y
800
35. f std − 80t 2 6t 2
36. f std − 10 1
45
t11
400
0
20
40
60
x
19–20 Use Definition 4 to find f 9sad at the given number a.
19. f sxd − s4x 1 1 ,
20. f sxd − 5x ,
4
38. A roast turkey is taken from an oven when its temperature has
reached 185°F and is placed on a table in a room where the
temperature is 75°F. The graph shows how the temperature of
the turkey decreases and eventually approaches room temperature. By measuring the slope of the tangent, estimate the rate
of change of the temperature after an hour.
a−6
a − 21
21–22 Use Equation 5 to find f 9sad at the given number a.
21. f sxd −
x2
,
x16
a−3
22. f sxd −
1
s2x 1 2
,
a−1
25. f std −
1
t2 1 1
T (°F)
200
23–26 Find f 9sad.
23. f sxd − 2x 2 2 5x 1 3
37. A warm can of soda is placed in a cold refrigerator. Sketch
the graph of the temperature of the soda as a function of time.
Is the initial rate of change of temperature greater or less than
the rate of change after an hour?
24. f std − t 3 2 3t
26. f sxd −
x
1 2 4x
27. Find an equation of the tangent line to the graph of y − Bsxd
at x − 6 if Bs6d − 0 and B9s6d − 2 12.
28. Find an equation of the tangent line to the graph of y − tsxd
at x − 5 if ts5d − 23 and t9s5d − 4.
P
100
0
30
60
90
120 150
t (min)
39. Sketch the graph of a function f for which f s0d − 0,
f 9s0d − 3, f 9s1d − 0, and f 9s2d − 21.
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SECTION 2.7
40. Sketch the graph of a function t for which
ts0d − ts2d − ts4d − 0, t9s1d − t9s3d − 0,
t9s0d − t9s4d − 1, t9s2d − 21, lim x l ` tsxd − `, and
lim x l 2` tsxd − 2`.
41. Sketch the graph of a function t that is continuous on its
domain s25, 5d and where ts0d − 1, t9s0d − 1, t9s22d − 0,
lim x l 251 tsxd − `, and lim x l52 tsxd − 3.
53. The quantity of oxygen that can dissolve in water depends on
the temperature of the water. (So thermal pollution influences
the oxygen content of water.) The graph shows how oxygen
solubility S varies as a function of the water temperature T.
(a) What is the meaning of the derivative S9sT d? What are its
units?
(b) Estimate the value of S9s16d and interpret it.
S (mg / L)
42. Sketch the graph of a function f where the domain is s22, 2d,
f 9s0d − 22, lim x l 22 f sxd − `, f is continuous at all numbers in its domain except 61, and f is odd.
16
12
43–48 Each limit represents the derivative of some function f at
some number a. State such an f and a in each case.
s9 1 h 2 3
43. lim
hl0
h
e221h 2 e22
44. lim
hl0
h
x 6 2 64
45. lim
x l2 x 2 2
1
24
x
46. lim
x l 1y4 x 2 1
4
S D
tan
47. lim
hl0
!
1h 21
4
h
48.
lim
" l !y6
1
sin " 2 2
"2
!
6
49. The cost (in dollars) of producing x units of a certain commodity is Csxd − 5000 1 10x 1 0.05x 2.
(a) Find the average rate of change of C with respect to x
when the production level is changed
(i) from x − 100 to x − 105
(ii) from x − 100 to x − 101
(b) Find the instantaneous rate of change of C with respect to
x when x − 100. (This is called the marginal cost. Its
significance will be explained in Section 3.7.)
50. Let H std be the daily cost (in dollars) to heat an office building when the outside temperature is t degrees Fahrenheit.
(a) What is the meaning of H9s58d? What are its units?
(b) Would you expect H9s58d to be positive or negative?
Explain.
51. The cost of producing x ounces of gold from a new gold mine
is C − f sxd dollars.
(a) What is the meaning of the derivative f 9sxd? What are its
units?
(b) What does the statement f 9s800d − 17 mean?
(c) Do you think the values of f 9sxd will increase or decrease
in the short term? What about the long term? Explain.
52. The quantity (in pounds) of a gourmet ground coffee that is
sold by a coffee company at a price of p dollars per pound
is Q − f s pd.
(a) What is the meaning of the derivative f 9s8d? What are its
units?
(b) Is f 9s8d positive or negative? Explain.
151
Derivatives and Rates of Change
8
4
0
8
16
24
32
40
T (°C)
Source: C. Kupchella et al., Environmental Science: Living Within
the System of Nature, 2d ed. (Boston: Allyn and Bacon, 1989).
54. The graph shows the influence of the temperature T on the
maximum sustainable swimming speed S of Coho salmon.
(a) What is the meaning of the derivative S9sT d? What are its
units?
(b) Estimate the values of S9s15d and S9s25d and interpret
them.
S (cm/s)
20
0
10
20
T (°C)
55. Researchers measured the average blood alcohol concentration Cstd of eight men starting one hour after consumption
of 30 mL of ethanol (corresponding to two alcoholic drinks).
t (hours)
1.0
1.5
2.0
2.5
3.0
Cstd sgydLd
0.033
0.024
0.018
0.012
0.007
(a) Find the average rate of change of C with respect to t
over each time interval:
(i) f1.0, 2.0g
(ii) f1.5, 2.0g
(iii) f2.0, 2.5g
(iv) f2.0, 3.0g
In each case, include the units.
(b) Estimate the instantaneous rate of change at t − 2 and
interpret your result. What are the units?
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of
Ethanol after Oral Administration in the Fasting State,” Journal of
Pharmacokinetics and Biopharmaceutics 5 (1977): 207–24.
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152
CHAPTER 2
Limits and Derivatives
56. The number N of locations of a popular coffeehouse chain is
given in the table. (The numbers of locations as of October 1
are given.)
Year
N
2008
2010
2012
2014
2016
16,680
16,858
18,066
21,366
25,085
(a) Find the average rate of growth
(i) from 2008 to 2010
(ii) from 2010 to 2012
In each case, include the units. What can you conclude?
(b) Estimate the instantaneous rate of growth in 2010 by
taking the average of two average rates of change.
What are its units?
(c) Estimate the instantaneous rate of growth in 2010 by
measuring the slope of a tangent.
57–58 Determine whether f 9s0d exists.
57. f sxd −
58. f sxd −
H
H
x sin
1
x
0
x 2 sin
0
if x ± 0
if x − 0
1
x
if x ± 0
if x − 0
WRITING PROJECT
1
; 59. (a) Graph the function f sxd − sin x 2 1000 sins1000xd in the
viewing rectangle f22!, 2!g by f24, 4g. What slope
does the graph appear to have at the origin?
(b) Zoom in to the viewing window f20.4, 0.4g by
f20.25, 0.25g and estimate the value of f 9s0d. Does
this agree with your answer from part (a)?
(c) Now zoom in to the viewing window f20.008, 0.008g by
f20.005, 0.005g. Do you wish to revise your estimate
for f 9s0d?
60. Symmetric Difference Quotients In Example 8 we approximated an instantaneous rate of change by averaging two average rates of change. An alternative method is to use a single
average rate of change over an interval centered at the desired
value. We define the symmetric difference quotient of a function f at x − a on the interval fa 2 d, a 1 d g as
f sa 1 d d 2 f sa 2 d d
f sa 1 d d 2 f sa 2 d d
−
sa 1 d d 2 sa 2 d d
2d
(a) Compute the symmetric difference quotient for the
function D in Example 8 on the interval f2004, 2012g
and verify that your result agrees with the estimate for
D9s2008d computed in the example.
(b) Show that the symmetric difference quotient of a function
f at x − a is equivalent to averaging the average rates of
change of f over the intervals fa 2 d, ag and fa, a 1 d g.
(c) Use a symmetric difference quotient to estimate
f 9s1d for f sxd − x 3 2 2x 2 1 2 with d − 0.4. Draw a
graph of f along with secant lines corresponding to
average rates of change over the intervals f1 2 d, 1g,
f1, 1 1 d g, and f1 2 d, 1 1 d g. Which of these secant
lines appears to have slope closest to that of the tangent
line at x − 1?
EARLY METHODS FOR FINDING TANGENTS
The first person to explicitly formulate the ideas of limits and derivatives was Sir Isaac
Newton in the 1660s. But Newton acknowledged that “If I have seen further than other men,
it is because I have stood on the shoulders of giants.” Two of those giants were Pierre Fermat
(1601–1665) and Newton’s mentor at Cambridge, Isaac Barrow (1630–1677). Newton was
familiar with the methods that these men used to find tangent lines, and their methods played a
role in Newton’s eventual formulation of calculus.
Learn about these methods by researching on the Internet or reading one of the references
listed here. Write an essay comparing the methods of either Fermat or Barrow to modern
methods. In particular, use the method of Section 2.7 to find an equation of the tangent line to
the curve y − x 3 1 2x at the point (1, 3) and show how either Fermat or Barrow would have
solved the same problem. Although you used derivatives and they did not, point out similarities between the methods.
1. C. H. Edwards, The Historical Development of the Calculus (New York: SpringerVerlag, 1979), pp. 124, 132.
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SECTION 2.8
The Derivative as a Function
153
2. Howard Eves, An Introduction to the History of Mathematics, 6th ed. (New York:
Saunders, 1990), pp. 391, 395.
3. Morris Kline, Mathematical Thought from Ancient to Modern Times (New York: Oxford
University Press, 1972), pp. 344, 346.
4. Uta Merzbach and Carl Boyer, A History of Mathematics, 3rd ed. (Hoboken, NJ: Wiley,
2011), pp. 323, 356.
2.8 The Derivative as a Function
■ The Derivative Function
In the preceding section we considered the derivative of a function f at a fixed number a:
1
f 9sad − lim
hl0
f sa 1 hd 2 f sad
h
Here we change our point of view and let the number a vary. If we replace a in Equation 1 by a variable x, we obtain
2
f 9sxd − lim
hl0
f sx 1 hd 2 f sxd
h
Given any number x for which this limit exists, we assign to x the number f 9sxd. So we
can regard f 9 as a new function, called the derivative of f and defined by Equation 2.
We know that the value of f 9 at x, f 9sxd, can be interpreted geometrically as the slope of
the tangent line to the graph of f at the point sx, f sxdd.
The function f 9 is called the derivative of f because it has been “derived” from f by
the limiting operation in Equation 2. The domain of f 9 is the set hx f 9sxd existsj and
may be smaller than the domain of f.
|
EXAMPLE 1 The graph of a function f is given in Figure 1. Use it to sketch the graph
of the derivative f 9.
y
y=ƒ
1
0
1
FIGURE 1
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x
154
CHAPTER 2
Limits and Derivatives
SOLUTION We can estimate the value of the derivative at any value of x by drawing the
tangent at the point sx, f sxdd and estimating its slope. For instance, for x − 3 we draw a
tangent at P in Figure 2 and estimate its slope to be about 2 23. (We have drawn a
triangle to help estimate the slope.) Thus f 9s3d < 2 23 < 20.67 and this allows us to
plot the point P9s3, 20.67d on the graph of f 9 directly beneath P. (The slope of the
graph of f becomes the y-value on the graph of f 9.)
y
D
1
A
m=0
m=1
C
2
mÅ_ 3
P
m=0
m=_1
y=ƒ
B
0
1
3
5
x
y
1
Cª
5
0
Bª
1
Dª
x
3
P ª(3, _0.67)
y=fª(x)
Aª
FIGURE 2
The slope of the tangent drawn at A appears to be about 21, so we plot the point A9
with a y-value of 21 on the graph of f 9 (directly beneath A). The tangents at B and D
are horizontal, so the derivative is 0 there and the graph of f 9 crosses the x-axis (where
y − 0) at the points B9 and D9, directly beneath B and D. Between B and D, the graph
of f is steepest at C and the tangent line there appears to have slope 1, so the largest
value of f 9sxd between B9 and D9 is 1 (at C9).
Notice that between B and D the tangents have positive slope, so f 9sxd is positive
there. (The graph of f 9 is above the x-axis.) But to the right of D the tangents have
negative slope, so f 9sxd is negative there. (The graph of f 9 is below the x-axis.)
n
EXAMPLE 2
(a) If f sxd − x 3 2 x, find a formula for f 9sxd.
(b) Illustrate this formula by comparing the graphs of f and f 9.
SOLUTION
(a) When using Equation 2 to compute a derivative, we must remember that the variable
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SECTION 2.8
2
is h and that x is temporarily regarded as a constant during the calculation of the limit.
f 9sxd − lim
f
hl0
_2
155
The Derivative as a Function
2
f sx 1 hd 2 f sxd
fsx 1 hd3 2 sx 1 hdg 2 fx 3 2 xg
− lim
hl0
h
h
x 3 1 3x 2h 1 3xh 2 1 h 3 2 x 2 h 2 x 3 1 x
hl0
h
− lim
_2
3x 2h 1 3xh 2 1 h 3 2 h
hl0
h
− lim
2
fª
− lim s3x 2 1 3xh 1 h 2 2 1d − 3x 2 2 1
hl0
2
_2
_2
(b) We use a calculator to graph f and f 9 in Figure 3. Notice that f 9sxd − 0 when f
has horizontal tangents and f 9sxd is positive when the tangents have positive slope. So
these graphs serve as a check on our work in part (a).
n
EXAMPLE 3 If f sxd − sx , find the derivative of f. State the domain of f 9.
FIGURE 3
SOLUTION
f 9sxd − lim
h l0
− lim
h l0
− lim
f sx 1 hd 2 f sxd
sx 1 h 2 sx
− lim
h
l
0
h
h
S
sx 1 h 2 sx sx 1 h 1 sx
?
h
sx 1 h 1 sx
D
sx 1 hd 2 x
h
(
h l 0 h sx 1 h 1 sx
1
− lim
h l 0 sx 1 h 1 sx
)
−
− lim
(Rationalize the numerator.)
(
h l 0 h sx 1 h 1 sx
)
1
1
−
2sx
sx 1 sx
We see that f 9sxd exists if x . 0, so the domain of f 9 is s0, `d. This is slightly smaller
y
than the domain of f , which is f0, `d.
n
Let’s check to see that the result of Example 3 is reasonable by looking at the graphs
1 close to 0, so f 9sxd − 1y(2 sx )
of f and f 9 in Figure 4. When x is close to 0, sx is also
is very large and this corresponds to the steep tangent lines near s0, 0d in Figure 4(a) and
x is very
the large values of f 9sxd just to the right of 0 in Figure 04(b). When
x is large, f 9sxd
1
small and this corresponds to the flatter tangent lines at the far right of the graph of f and
the horizontal asymptote of the graph of f 9.
(a) ƒ=œ„
x
y
y
1
1
0
FIGURE 4
1
x
0
1
x
1
(b) f ª (x)=
2œ„
x
(a) ƒ=œ„
x
y
1
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0
x
156
CHAPTER 2
Limits and Derivatives
EXAMPLE 4 Find f 9 if f sxd −
12x
.
21x
SOLUTION
f sx 1 hd 2 f sxd
h
1 2 sx 1 hd
12x
2
2 1 sx 1 hd
21x
− lim
hl0
h
f 9sxd − lim
hl0
a
c
2
b
d
ad 2 bc 1
−
!
e
bd
e
s1 2 x 2 hds2 1 xd 2 s1 2 xds2 1 x 1 hd
hl0
hs2 1 x 1 hds2 1 xd
− lim
s2 2 x 2 2h 2 x 2 2 xhd 2 s2 2 x 1 h 2 x 2 2 xhd
hl0
hs2 1 x 1 hds2 1 xd
− lim
Leibniz
Gottfried Wilhelm Leibniz was born in
Leipzig in 1646 and studied law, theology, philosophy, and mathematics at
the university there, graduating with
a bachelor’s degree at age 17. After
earning his doctorate in law at age 20,
Leibniz entered the diplomatic service
and spent most of his life traveling to
the capitals of Europe on political missions. In particular, he worked to avert
a French military threat against Germany and attempted to reconcile the
Catholic and Protestant churches.
His serious study of mathematics
did not begin until 1672 while he was
on a diplomatic mission in Paris. There
he built a calculating machine and
met scientists, like Huygens, who
directed his attention to the latest
developments in mathematics and
science. Leibniz sought to develop a
symbolic logic and system of notation
that would simplify logical reasoning.
In particular, the version of calculus
that he published in 1684 established
the notation and the rules for finding
derivatives that we use today.
Unfortunately, a dreadful priority
dispute arose in the 1690s between
the followers of Newton and those of
Leibniz as to who had invented calculus first. Leibniz was even accused of
plagiarism by members of the Royal
Society in England. The truth is that
each man invented calculus independently. Newton arrived at his version
of calculus first but, because of his
fear of controversy, did not publish
it immediately. So Leibniz’s 1684
account of calculus was the first to be
published.
23h
hs2 1 x 1 hds2 1 xd
23
3
− lim
−2
h l 0 s2 1 x 1 hds2 1 xd
s2 1 xd2
− lim
hl0
n
■ Other Notations
If we use the traditional notation y − f sxd to indicate that the independent variable is x
and the dependent variable is y, then some common alternative notations for the derivative are as follows:
f 9sxd − y9 −
dy
df
d
−
−
f sxd − D f sxd − Dx f sxd
dx
dx
dx
The symbols D and dydx are called differentiation operators because they indicate the
operation of differentiation, which is the process of calculating a derivative.
The symbol dyydx, which was introduced by Leibniz, should not be regarded as a
ratio (for the time being); it is simply a synonym for f 9sxd. Nonetheless, it is a very useful
and suggestive notation, especially when used in conjunction with increment notation.
Referring to Equation 2.7.6, we can rewrite the definition of derivative in Leibniz notation in the form
dy
Dy
− lim
Dx l 0 Dx
dx
If we want to indicate the value of a derivative dyydx in Leibniz notation at a specific
number a, we use the notation
Z
dy
dx x−a
or
dy
dx
G
x−a
which is a synonym for f 9sad. The vertical bar means “evaluate at.”
3 Definition A function f is differentiable at a if f 9sad exists. It is differentiable on an open interval sa, bd [or sa, `d or s2`, ad or s2`, `d] if it is differentiable at every number in the interval.
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SECTION 2.8
The Derivative as a Function
157
EXAMPLE 5 Where is the function f sxd − | x | differentiable?
| |
SOLUTION If x . 0, then x − x and we can choose h small enough that x 1 h . 0
and hence x 1 h − x 1 h. Therefore, for x . 0, we have
|
|
f 9sxd − lim
hl0
− lim
| x 1 h | 2 | x | − lim sx 1 hd 2 x
h
h
hl0 h
hl0
h
− lim 1 − 1
hl0
and so f is differentiable for any x . 0.
Similarly, for x , 0 we have x − 2x and h can be chosen small enough that
x 1 h , 0 and so x 1 h − 2sx 1 hd. Therefore, for x , 0,
|
| |
|
f 9sxd − lim
hl0
− lim
hl0
| x 1 h | 2 | x | − lim 2sx 1 hd 2 s2xd
h
h
hl0
2h
− lim s21d − 21
hl0
h
and so f is differentiable for any x , 0.
For x − 0 we have to investigate
f 9s0d − lim
hl0
− lim
hl0
f s0 1 hd 2 f s0d
h
| 0 1 h | 2 | 0 | − lim | h |
h
hl0
h
(if it exists)
Let’s compute the left and right limits separately:
lim
| h | − lim h − lim 1 − 1
lim
| h | − lim 2h − lim s21d − 21
h l 01
y
and
0
x
h
h l 01 h
h l 02
y
h l 01
h
h l 02
Since these limits are different, f 9s0d does not exist. Thus f is differentiable at all x
except 0.
A formula for f 9 is given by
f 9sxd −
(a) y=ƒ=| x |
H
1
if x . 0
21 if x , 0
and its graph is shown in Figure 5(b). The fact that f 9s0d does not exist is reflected
geometrically in the fact that the curve y − x does not have a tangent line at s0, 0d.
[See Figure 5(a).]
n
| |
1
0
x
_1
(b) y=fª(x)
FIGURE 5
h l 02
h
Both continuity and differentiability are desirable properties for a function to have.
The following theorem shows how these properties are related.
4 Theorem If f is differentiable at a, then f is continuous at a.
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158
CHAPTER 2
Limits and Derivatives
PROOF To prove that f is continuous at a, we have to show that lim x l a f sxd − f sad.
We will do this by showing that the difference f sxd 2 f sad approaches 0.
The given information is that f is differentiable at a, that is,
f 9sad − lim
xla
PS An important aspect of problem solving
is trying to find a connection between the
given and the unknown. See Step 2 (Think
of a Plan) in Principles of Problem Solving
following Chapter 1.
f sxd 2 f sad
x2a
exists (see Equation 2.7.5). To connect the given and the unknown, we divide and
multiply f sxd 2 f sad by x 2 a (which we can do when x ± a):
f sxd 2 f sad −
f sxd 2 f sad
sx 2 ad
x2a
Thus, using Limit Law 4, we can write
lim f f sxd 2 f sadg − lim
xla
xla
− lim
xla
f sxd 2 f sad
sx 2 ad
x2a
f sxd 2 f sad
? lim sx 2 ad
xla
x2a
− f 9sad ? 0 − 0
To use what we have just proved, we start with f sxd and add and subtract f sad:
lim f sxd − lim f f sad 1 s f sxd 2 f saddg
xla
xla
− lim f sad 1 lim f f sxd 2 f sadg
xla
xla
− f sad 1 0 − f sad
Therefore f is continuous at a.
n
NOTE The converse of Theorem 4 is false; that is, there are functions that are continuous but not differentiable. For instance, the function f sxd − x is continuous at 0
because
lim f sxd − lim x − 0 − f s0d
| |
xl0
xl0
| |
(See Example 2.3.7.) But in Example 5 we showed that f is not differentiable at 0.
■ How Can a Function Fail To Be Differentiable?
| |
We saw that the function y − x in Example 5 is not differentiable at 0 and Figure 5(a)
shows that its graph changes direction abruptly when x − 0. In general, if the graph of a
function f has a “corner” or “kink” in it, then the graph of f has no tangent at this point
and f is not differentiable there. [In trying to compute f 9sad, we find that the left and right
limits are different.]
Theorem 4 gives another way for a function not to have a derivative. It says that if f
is not continuous at a, then f is not differentiable at a. So at any discontinuity (for
instance, a jump discontinuity) f fails to be differentiable.
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SECTION 2.8
y
The Derivative as a Function
159
A third possibility is that the curve has a vertical tangent line when x − a; that is, f
is continuous at a and
vertical tangent line
|
|
lim f 9sxd − `
xla
0
a
x
This means that the tangent lines become steeper and steeper as x l a. Figure 6 shows
one way that this can happen; Figure 7(c) shows another. Figure 7 illustrates the three
possibilities that we have discussed.
y
FIGURE 6
y
0
FIGURE 7
Three ways for f not to be
differentiable at a
a
y
0
x
(a) A corner
a
x
0
(b) A discontinuity
a
x
(c) A vertical tangent
A graphing calculator or computer provides another way of looking at differentiability. If f is differentiable at a, then when we zoom in toward the point sa, f sadd the graph
straightens out and appears more and more like a line. (See Figure 8. We saw a specific
example of this in Figure 2.7.2.) But no matter how much we zoom in toward a point like
the ones in Figures 6 and 7(a), we can’t eliminate the sharp point or corner (see Figure 9).
y
0
y
a
0
x
a
FIGURE 8
FIGURE 9
f is differentiable at a.
f is not differentiable at a.
x
■ Higher Derivatives
If f is a differentiable function, then its derivative f 9 is also a function, so f 9 may have a
derivative of its own, denoted by s f 9d9 − f 0. This new function f 0 is called the second
derivative of f because it is the derivative of the derivative of f. Using Leibniz notation,
we write the second derivative of y − f sxd as
d
dx
S D
derivative
of
first
derivative
dy
dx
−
d 2y
dx 2
second
derivative
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160
CHAPTER 2
Limits and Derivatives
EXAMPLE 6 If f sxd − x 3 2 x, find and interpret f 0sxd.
SOLUTION In Example 2 we found that the first derivative is f 9sxd − 3x 2 2 1. So the
second derivative is
f 9sx 1 hd 2 f 9sxd
h
f3sx 1 hd2 2 1g 2 f3x 2 2 1g
− lim
h l0
h
3x 2 1 6xh 1 3h 2 2 1 2 3x 2 1 1
− lim
h l0
h
f 99sxd − s f 9d9sxd − lim
h l0
− lim s6x 1 3hd − 6x
h l0
The graphs of f , f 9, and f 0 are shown in Figure 10.
2
f·
fª
f
_1.5
1.5
FIGURE 10
_2
We can interpret f 0sxd as the slope of the curve y − f 9sxd at the point sx, f 9sxdd. In
other words, it is the rate of change of the slope of the original curve y − f sxd.
Notice from Figure 10 that f 0sxd is negative when y − f 9sxd has negative slope
and positive when y − f 9sxd has positive slope. So the graphs serve as a check on our
calculations.
n
In general, we can interpret a second derivative as a rate of change of a rate of change.
The most familiar example of this is acceleration, which we define as follows.
If s − sstd is the position function of an object that moves in a straight line, we know
that its first derivative represents the velocity v std of the object as a function of time:
v std − s9std −
ds
dt
The instantaneous rate of change of velocity with respect to time is called the acceleration astd of the object. Thus the acceleration function is the derivative of the velocity
function and is therefore the second derivative of the position function:
astd − v9std − s0std
or, in Leibniz notation,
a−
dv
d 2s
− 2
dt
dt
Acceleration is the change in velocity you feel when speeding up or slowing down in a car.
The third derivative f - is the derivative of the second derivative: f -− s f 0d9. So
f -sxd can be interpreted as the slope of the curve y − f 0sxd or as the rate of change of
f 0sxd. If y − f sxd, then alternative notations for the third derivative are
y- − f -sxd −
d
dx
S D
d2y
dx 2
−
d 3y
dx 3
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SECTION 2.8
The Derivative as a Function
161
We can also interpret the third derivative physically in the case where the function
is the position function s − sstd of an object that moves along a straight line. Because
s-− ss0d9 − a9, the third derivative of the position function is the derivative of the acceleration function and is called the jerk:
j−
da
d 3s
− 3
dt
dt
Thus the jerk j is the rate of change of acceleration. It is aptly named because a large jerk
means a sudden change in acceleration, which causes an abrupt movement.
The differentiation process can be continued. The fourth derivative f + is usually
denoted by f s4d. In general, the nth derivative of f is denoted by f snd and is obtained from
f by differentiating n times. If y − f sxd, we write
y snd − f sndsxd −
dny
dx n
EXAMPLE 7 If f sxd − x 3 2 x, find f -sxd and f s4dsxd.
SOLUTION In Example 6 we found that f 0sxd − 6x. The graph of the second derivative
has equation y − 6x and so it is a straight line with slope 6. Since the derivative f -sxd
is the slope of f 0sxd, we have
f -sxd − 6
for all values of x. So f - is a constant function and its graph is a horizontal line.
Therefore, for all values of x,
f s4dsxd − 0
n
We have seen that one application of second and third derivatives occurs in analyzing
the motion of objects using acceleration and jerk. We will investigate another application of second derivatives in Section 4.3, where we show how knowledge of f 0 gives us
information about the shape of the graph of f. In Chapter 11 we will see how second and
higher derivatives enable us to represent functions as sums of infinite series.
2.8 Exercises
1–2 Use the given graph to estimate the value of each derivative.
Then sketch the graph of f 9.
1. (a) f 9s0d
(e) f 9s4d
(b) f 9s1d
(f ) f 9s5d
(c) f 9s2d
(g) f 9s6d
y
(b) f 9s22d
(e) f 9s1d
1
1
0
1
(c) f 9s21d
(f ) f 9s2d
y
y=ƒ
y=ƒ
0
(d) f 9s3d
(h) f 9s7d
2. (a) f 9s23d
(d) f 9s0d
(g) f 9s3d
1
x
x
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162
CHAPTER 2
Limits and Derivatives
3. Match the graph of each function in (a) – (d) with the graph of
its derivative in I–IV. Give reasons for your choices.
y
(a)
8.
y
(b)
0
0
x
0
(c)
x
0
y
I
y
y
11.
0
x
x
0
x
0
y
II
0
x
y
(d)
0
x
x
10.
y
y
9.
y
x
12. Shown is the graph of the population function Pstd for yeast
cells in a laboratory culture. Use the method of Example 1 to
graph the derivative P9std. What does the graph of P9 tell us
about the yeast population?
x
P (yeast cells)
y
III
0
500
y
IV
x
0
0
x
y
5.
15 t (hours)
10
13. A rechargeable battery is plugged into a charger. The graph
shows Cstd, the percentage of full capacity that the battery
reaches as a function of time t elapsed (in hours).
(a) What is the meaning of the derivative C9std?
(b) Sketch the graph of C9std. What does the graph tell you?
4–11 Trace or copy the graph of the given function f. (Assume
that the axes have equal scales.) Then use the method of
Example 1 to sketch the graph of f 9 below it.
4.
5
C
y
100
80
0
0
x
Percentage
of full charge
x
60
40
20
0
6.
y
0
7.
2
4
6
8
10 12
t (hours)
y
x
0
x
14. The graph (from the US Department of Energy) shows
how driving speed affects gas mileage. Fuel economy F
is measured in miles per gallon and speed v is measured in
miles per hour.
(a) What is the meaning of the derivative F9svd?
(b) Sketch the graph of F9svd.
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SECTION 2.8
(c) At what speed should you drive if you want to save
on gas?
30
21. f sxd − 3x 2 8
22. f sxd − mx 1 b
23. f std − 2.5t 1 6t
24. f sxd − 4 1 8x 2 5x 2
25. As pd − 4p 3 1 3p
26. F std − t 3 2 5t 1 1
2
20
10
10
20
30
40
50
60
70
√ (mi/h)
15. The graph shows how the average surface water temperature
f of Lake Michigan varies over the course of a year (where
t is measured in months with t − 0 corresponding to January 1). The average was calculated from data obtained over
a 20-year period ending in 2011. Sketch the graph of the
derivative function f 9. When is f 9std largest?
f (°F)
70
60
50
40
2
4
6
8
10
12
t (months)
16–18 Make a careful sketch of the graph of f and below it
sketch the graph of f 9 in the same manner as in Exercises 4 –11.
Can you guess a formula for f 9sxd from its graph?
16. f sxd − sin x
17. f sxd − e x
18. f sxd − ln x
; 19. Let f sxd − x .
(a) Estimate the values of f 9s0d, f 9( 12 ), f 9s1d, and f 9s2d by
zooming in on the graph of f.
(b) Use symmetry to deduce the values of f 9(221 ), f 9s21d,
and f 9s22d.
(c) Use the results from parts (a) and (b) to guess a formula
for f 9sxd.
(d) Use the definition of derivative to prove that your guess
in part (c) is correct.
27. f sxd −
1
x2 2 4
28. Fsvd −
29. tsud −
u11
4u 2 1
30. f sxd − x 4
31. f sxd −
1
s1 1 x
32. tsxd −
v
v12
1
1 1 sx
33. (a) Sketch the graph of f sxd − 1 1 sx 1 3 by starting
with the graph of y − s x and using the transformations
of Section 1.3.
(b) Use the graph from part (a) to sketch the graph of f 9.
(c) Use the definition of a derivative to find f 9sxd. What are
the domains of f and f 9?
(d) Graph f 9 and compare with your sketch in part (b).
;
;
0
163
21–32 Find the derivative of the function using the definition of
derivative. State the domain of the function and the domain of its
derivative.
F (mi/gal)
0
The Derivative as a Function
34. (a) If f sxd − x 1 1yx, find f 9sxd.
(b) Check to see that your answer to part (a) is reasonable
by comparing the graphs of f and f 9.
35. (a) If f sxd − x 4 1 2x, find f 9sxd.
(b) Check to see that your answer to part (a) is reasonable
;
by comparing the graphs of f and f 9.
36. The table gives the number Nstd, measured in thousands, of
minimally invasive cosmetic surgery procedures performed
in the United States for various years t.
2
; 20. Let f sxd − x .
(a) Estimate the values of f 9s0d, f 9( 12 ), f 9s1d, f 9s2d, and
f 9s3d by zooming in on the graph of f.
(b) Use symmetry to deduce the values of f 9(221 ), f 9s21d,
f 9s22d, and f 9s23d.
(c) Use the values from parts (a) and (b) to graph f 9.
(d) Guess a formula for f 9sxd.
(e) Use the definition of derivative to prove that your guess
in part (d) is correct.
3
t
Nstd (thousands)
2000
2002
2004
2006
2008
2010
2012
2014
5,500
4,897
7,470
9,138
10,897
11,561
13,035
13,945
Source: American Society of Plastic Surgeons
(a) What is the meaning of N9std? What are its units?
(b) Construct a table of estimated values for N9std.
(c) Graph N and N9.
(d) How would it be possible to get more accurate values
for N9std?
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164
CHAPTER 2
Limits and Derivatives
37. The table gives the height as time passes of a typical pine tree
grown for lumber at a managed site.
Tree age (years)
14
21
28
35
42
49
Height (feet)
41
54
64
72
78
83
43. y
0
2
4
6
x
_2
Source: Arkansas Forestry Commission
If Hstd is the height of the tree after t years, construct a table
of estimated values for H9 and sketch its graph.
38. Water temperature affects the growth rate of brook trout.
The table shows the amount of weight gained by brook trout
after 24 days in various water temperatures.
Temperature (°C)
15.5
17.7
20.0
22.4
24.4
Weight gained (g)
37.2
31.0
19.8
9.7
29.8
y
44.
0
2
4 x
| |
; 45. Graph the function f sxd − x 1 s x . Zoom in repeatedly,
first toward the point (21, 0) and then toward the origin.
What is different about the behavior of f in the vicinity of
these two points? What do you conclude about the differentiability of f ?
; 46. Zoom in toward the points (1, 0), (0, 1), and (21, 0) on the
graph of the function tsxd − sx 2 2 1d2y3. What do you
notice? Account for what you see in terms of the differentiability of t.
47–48 The graphs of a function f and its derivative f 9 are shown.
Which is bigger, f 9s21d or f 99s1d ?
47.
y
If Wsxd is the weight gain at temperature x, construct a table
of estimated values for W9 and sketch its graph. What are the
units for W9sxd?
0
Source: Adapted from J. Chadwick Jr., “Temperature Effects on Growth
and Stress Physiology of Brook Trout: Implications for Climate Change
Impacts on an Iconic Cold-Water Fish.” Masters Theses. Paper 897. 2012.
scholarworks.umass.edu/theses/897.
39. Let P represent the percentage of a city’s electrical
power that is produced by solar panels t years after
January 1, 2020.
(a) What does dPydt represent in this context?
(b) Interpret the statement
dP
dt
Z
48.
42.
_2
0
2
x
y
y
_2
x
1
49. The figure shows the graphs of f , f 9, and f 0. Identify each
curve, and explain your choices.
41–44 The graph of f is given. State, with reasons, the numbers
at which f is not differentiable.
y
x
y
0
− 3.5
t −2
40. Suppose N is the number of people in the United States
who travel by car to another state for a vacation in a
year when the average price of gasoline is p dollars per
gallon. Do you expect dNydp to be positive or negative?
Explain.
41.
1
a
b
2
4
x
c
x
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SECTION 2.8
50. The figure shows graphs of f, f 9, f 0, and f -. Identify each
curve, and explain your choices.
y
a b c d
165
The Derivative as a Function
56. (a) The graph of a position function of a car is shown,
where s is measured in feet and t in seconds. Use it to
graph the velocity and acceleration of the car. What is
the acceleration at t − 10 seconds?
s
x
100
0
51. The figure shows the graphs of three functions. One is the
position function of a car, one is the velocity of the car, and
one is its acceleration. Identify each curve, and explain your
choices.
y
a
b
c
20
t
(b) Use the acceleration curve from part (a) to estimate the
jerk at t − 10 seconds. What are the units for jerk?
3
x.
57. Let f sxd − s
(a) If a ± 0, use Equation 2.7.5 to find f 9sad.
(b) Show that f 9s0d does not exist.
3
(c) Show that y − s
x has a vertical tangent line at s0, 0d.
(Recall the shape of the graph of f . See Figure 1.2.13.)
58. (a) If tsxd − x 2y3, show that t9s0d does not exist.
(b) If a ± 0, find t9sad.
(c) Show that y − x 2y3 has a vertical tangent line at s0, 0d.
(d) Illustrate part (c) by graphing y − x 2y3.
;
t
0
10
|
|
59. Show that the function f sxd − x 2 6 is not differentiable
at 6. Find a formula for f 9 and sketch its graph.
52. The figure shows the graphs of four functions. One is the
position function of a car, one is the velocity of the car, one
is its acceleration, and one is its jerk. Identify each curve,
and explain your choices.
y
0
b
| |
c
t
; 53–54 Use the definition of a derivative to find f 9sxd and f 0sxd.
Then graph f , f 9, and f 0 on a common screen and check to see
if your answers are reasonable.
53. f sxd − 3x 2 1 2x 1 1
| |
61. (a) Sketch the graph of the function f sxd − x x .
(b) For what values of x is f differentiable?
(c) Find a formula for f 9.
62. (a) Sketch the graph of the function tsxd − x 1 x .
(b) For what values of x is t differentiable?
(c) Find a formula for t9.
d
a
60. Where is the greatest integer function f sxd − v x b not differentiable? Find a formula for f 9 and sketch its graph.
63. Derivatives of Even and Odd Functions Recall that a function f is called even if f s2xd − f sxd for all x in its domain
and odd if f s2xd − 2f sxd for all such x. Prove each of the
following.
(a) The derivative of an even function is an odd function.
(b) The derivative of an odd function is an even function.
64–65 Left- and Right-Hand Derivatives The left-hand and
right-hand derivatives of f at a are defined by
54. f sxd − x 3 2 3x
2
3
s4d
; 55. If f sxd − 2x 2 x , find f 9sxd, f 0sxd, f -sxd, and f sxd.
Graph f , f 9, f 0, and f - on a common screen. Are the
graphs consistent with the geometric interpretations of
these derivatives?
f sa 1 hd 2 f sad
h
f sa 1 hd 2 f sad
f 91 sad − lim1
hl0
h
f 92 sad − lim2
hl0
and
if these limits exist. Then f 9sad exists if and only if these onesided derivatives exist and are equal.
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166
CHAPTER 2
Limits and Derivatives
64. Find f 92s0d and f 91s0d for the given function f. Is f differentiable at 0?
(a)
f sxd −
(b)
f sxd −
H
H
0 if x < 0
x if x . 0
0 if x < 0
x 2 if x . 0
67. Nick starts jogging and runs faster and faster for 3 mintues,
then he walks for 5 minutes. He stops at an intersection for
2 minutes, runs fairly quickly for 5 minutes, then walks for
4 minutes.
(a) Sketch a possible graph of the distance s Nick has
covered after t minutes.
(b) Sketch a graph of dsydt.
65. Let
0
52x
f sxd −
1
52x
if x < 0
if 0 , x , 4
if x > 4
(a) Find f 92s4d and f 91s4d.
(b) Sketch the graph of f.
(c) Where is f discontinuous?
(d) Where is f not differentiable?
2
66. When you turn on a hot-water faucet, the temperature T of the
water depends on how long the water has been running. In
Example 1.1.4 we sketched a possible graph of T as a function
of the time t that has elapsed since the faucet was turned on.
(a) Describe how the rate of change of T with respect to t
varies as t increases.
(b) Sketch a graph of the derivative of T.
68. Let ! be the tangent line to the parabola y − x 2 at the
point s1, 1d. The angle of inclination of ! is the angle $
that ! makes with the positive direction of the x-axis.
Calculate $ correct to the nearest degree.
REVIEW
CONCEPT CHECK
Answers to the Concept Check are available at StewartCalculus.com.
1. Explain what each of the following means and illustrate with
a sketch.
(a) lim f sxd − L
(b) lim1 f sxd − L (c) lim2 f sxd − L
x la
(d) lim f sxd − `
x la
x la
x la
(e) lim f sxd − L
x l`
2. Describe several ways in which a limit can fail to exist.
Illustrate with sketches.
3. State the following Limit Laws.
(a) Sum Law
(b) Difference Law
(c) Constant Multiple Law
(d) Product Law
(e) Quotient Law
(f ) Power Law
(g) Root Law
4. What does the Squeeze Theorem say?
5. (a) What does it mean to say that the line x − a is a vertical
asymptote of the curve y − f sxd? Draw curves to illustrate the various possibilities.
(b) What does it mean to say that the line y − L is a horizontal asymptote of the curve y − f sxd? Draw curves to
illustrate the various possibilities.
6. Which of the following curves have vertical asymptotes?
Which have horizontal asymptotes?
(a) y − x 4
(b) y − sin x
(c) y − tan x
(d) y − tan21x
(e) y − e x
(f ) y − ln x
(g) y − 1yx
(h) y − sx
7. (a) What does it mean for f to be continuous at a?
(b) What does it mean for f to be continuous on the
interval s2`, `d? What can you say about the graph
of such a function?
8. (a) Give examples of functions that are continuous
on f21, 1g.
(b) Give an example of a function that is not continuous
on f0, 1g.
9. What does the Intermediate Value Theorem say?
10. Write an expression for the slope of the tangent line to the
curve y − f sxd at the point sa, f sadd.
11. Suppose an object moves along a straight line with position f std at time t. Write an expression for the instantaneous velocity of the object at time t − a. How can you
interpret this velocity in terms of the graph of f ?
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CHAPTER 2
Review
167
12. If y − f sxd and x changes from x 1 to x 2, write expressions for
the following.
14. Define the second derivative of f. If f std is the position function of a particle, how can you interpret the second derivative?
(a) The average rate of change of y with respect to x over the
interval fx 1, x 2 g
15. (a) What does it mean for f to be differentiable at a?
(b) What is the relation between the differentiability and
continuity of a function?
(c) Sketch the graph of a function that is continuous but not
differentiable at a − 2.
(b) The instantaneous rate of change of y with respect to x
at x − x 1
13. Define the derivative f 9sad. Discuss two ways of interpreting
this number.
16. Describe several ways in which a function can fail to be
differentiable. Illustrate with sketches.
TRUE-FALSE QUIZ
Determine whether the statement is true or false. If it is true,
explain why. If it is false, explain why or give an example that
disproves the statement.
1. lim
x l4
S
2x
8
2
x24
x24
D
− lim
2x
x l4 x 2 4
2 lim
8
x l4 x 2 4
lim sx 2 1 6x 2 7d
x 2 1 6x 2 7
x l1
2. lim 2
−
x l 1 x 1 5x 2 6
lim sx 2 1 5x 2 6d
x l1
lim sx 2 3d
x23
xl1
3. lim 2
−
x l 1 x 1 2x 2 4
lim sx 2 1 2x 2 4d
xl1
x2 2 9
4.
−x13
x23
2
x 29
− lim sx 1 3d
xl3 x 2 3
xl3
5. lim
6. If lim x l 5 f sxd − 2 and lim x l 5 tsxd − 0, then
limx l 5 f f sxdytsxdg does not exist.
12. A function can have two different horizontal asymptotes.
13. If f has domain f0, `d and has no horizontal asymptote, then
lim x l ` f sxd − ` or lim x l ` f sxd − 2`.
14. If the line x − 1 is a vertical asymptote of y − f sxd, then f is
not defined at 1.
15. If f s1d . 0 and f s3d , 0, then there exists a number c
between 1 and 3 such that f scd − 0.
16. If f is continuous at 5 and f s5d − 2 and f s4d − 3, then
lim x l 2 f s4x 2 2 11d − 2.
17. If f is continuous on f21, 1g and f s21d − 4 and f s1d − 3,
then there exists a number r such that r , 1 and f srd − !.
| |
18. Let f be a function such that lim x l 0 f sxd − 6. Then there
exists a positive number # such that if 0 , x , #, then
f sxd 2 6 , 1.
|
| |
|
19. If f sxd . 1 for all x and lim x l 0 f sxd exists, then
lim x l 0 f sxd . 1.
20. If f is continuous at a, then f is differentiable at a.
7. If lim x l5 f sxd − 0 and lim x l 5 tsxd − 0, then
lim x l 5 f f sxdytsxdg does not exist.
21. If f 9srd exists, then lim x l r f sxd − f srd.
8. If neither lim x l a f sxd nor lim x l a tsxd exists, then
lim x l a f f sxd 1 tsxdg does not exist.
22.
9. If lim x l a f sxd exists but lim x l a tsxd does not exist, then
lim x l a f f sxd 1 tsxdg does not exist.
10. If p is a polynomial, then lim x l b psxd − psbd.
11. If lim x l 0 f sxd − ` and lim x l 0 tsxd − `, then
lim x l 0 f f sxd 2 tsxdg − 0.
d 2y
−
dx 2
S D
dy
dx
2
23. The equation x 10 2 10x 2 1 5 − 0 has a solution in the
interval s0, 2d.
| |
24. If f is continuous at a, so is f .
| |
25. If f is continuous at a, so is f .
| |
26. If f is differentiable at a, so is f .
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168
CHAPTER 2
Limits and Derivatives
EXERCISES
1. The graph of f is given.
19. lim1 tan21s1yxd
20. lim
x l0
y
xl1
S
1
1
1 2
x21
x 2 3x 1 2
D
; 21–22 Use graphs to discover the asymptotes of the curve. Then
prove what you have discovered.
21. y −
1
0
x
1
cos2 x
x2
22. y − sx 2 1 x 1 1 2 sx 2 2 x
23. If 2x 2 1 < f sxd < x 2 for 0 , x , 3, find lim x l1 f sxd.
24. Prove that lim x l 0 x 2 coss1yx 2 d − 0.
(a) Find each limit, or explain why it does not exist.
(i) lim1 f sxd
(ii) lim 1 f sxd (iii) lim f sxd
x l2
x l 23
x l 23
(iv) lim f sxd
(v) lim f sxd
(vi) lim2 f sxd
(vii) lim f sxd
(viii) lim f sxd
x l4
x l`
x l0
x l2
x l 2`
lim f sxd − 2`,
x l 32
3
26. lim s
x −0
27. lim sx 2 2 3xd − 22
28. lim1
xl2
29. Let
2. Sketch the graph of a function f that satisfies all of the following conditions:
lim f sxd − 22, lim f sxd − 0, lim f sxd − `,
xl`
25. lim s14 2 5xd − 4
x l 23
lim f sxd − 2,
x l 31
2
5. lim
x 29
x l 23 x 2 1 2x 2 3
sh 2 1d3 1 1
hl0
h
7. lim
9. lim
sr
r l 9 sr 2 9d4
r 2 2 3r 2 4
11. lim
r l 21 4r 2 1 r 2 3
sx 2 2 9
x l ` 2x 2 6
13. lim
x l1
t2 2 4
t l2 t3 2 8
xl!
10. lim1
vl4
|
42v
42v
|
17. lim (sx 2 1 4x 1 1 2 x)
xl`
(iv) lim2 f sxd
(v) lim1 f sxd
x l3
(iii) lim f sxd
xl0
(vi) lim f sxd
x l3
2x 2 x 2
22x
x24
!
if 0 < x < 2
if 2 , x < 3
if 3 , x , 4
if x > 4
31–32 Show that the function is continuous on its domain. State
the domain.
sx 2 2 9
31. hsxd − xe sin x
32. tsxd − 2
x 22
3 2 st 1 4
12. lim
tl5
t25
16.
xl0
(a) For each of the numbers 2, 3, and 4, determine whether t
is continuous from the left, continuous from the right, or
continuous at the number.
(b) Sketch the graph of t.
sx 2 2 9
x l 2` 2x 2 6
lim
2
15. lim2 lnssin xd
xl0
tsxd −
x 29
x 1 2x 2 3
2
8. lim
14.
H
30. Let
2
2
6. lim1
−`
sx 2 4
(b) Where is f discontinuous?
(c) Sketch the graph of f.
x2 2 9
x l 3 x 1 2x 2 3
4. lim
2
if x , 0
s2x
f sxd − 3 2 x
if 0 < x , 3
sx 2 3d2 if x . 3
x l3
3–20 Find the limit.
xl0
xl4
(a) Evaluate each limit, if it exists.
(ii) lim2 f sxd
(i) lim1 f sxd
f is continuous from the right at 3
3. lim cossx 3 1 3xd
xl0
xl2
(b) State the equations of the horizontal asymptotes.
(c) State the equations of the vertical asymptotes.
(d) At what numbers is f discontinuous? Explain.
x l 2`
25–28 Prove the statement using the precise definition of a limit.
lim
x l 2`
4
1 2 2x 2 x
5 1 x 2 3x 4
18. lim e x 2x
2
33–34 Use the Intermediate Value Theorem to show that there is
a solution of the equation in the given interval.
33. x 5 2 x 3 1 3x 2 5 − 0,
34. cos sx − e 2 2,
x
s1, 2d
s0, 1d
xl`
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CHAPTER 2
35. (a) Find the slope of the tangent line to the curve
y − 9 2 2x 2 at the point s2, 1d.
(b) Find an equation of this tangent line.
y
44.
x
0
36. Find equations of the tangent lines to the curve
y−
169
Review
2
1 2 3x
at the points with x-coordinates 0 and 21.
45–46 Find the derivative of f using the definition of a
derivative. What is the domain of f 9?
37. The displacement (in meters) of an object moving in a
straight line is given by s − 1 1 2t 1 14 t 2, where t is measured in seconds.
(a) Find the average velocity over each time period.
(i) f1, 3g (ii) f1, 2g (iii) f1, 1.5g (iv) f1, 1.1g
(b) Find the instantaneous velocity when t − 1.
45. f sxd −
2
x2
46. f std −
1
st 1 1
47. (a) If f sxd − s3 2 5x , use the definition of a derivative
to find f 9sxd.
(b) Find the domains of f and f 9.
(c) Graph f and f 9 on a common screen. Compare the
;
graphs to see whether your answer to part (a) is
reasonable.
38. According to Boyle’s Law, if the temperature of a confined
gas is held fixed, then the product of the pressure P and the
volume V is a constant. Suppose that, for a certain gas,
PV − 800, where P is measured in pounds per square inch
and V is measured in cubic inches.
(a) Find the average rate of change of P as V increases
from 200 in3 to 250 in3.
(b) Express V as a function of P and show that the instantaneous rate of change of V with respect to P is
inversely proportional to the square of P.
48. (a) Find the asymptotes of the graph of
f sxd −
39. (a) Use the definition of a derivative to find f 9s2d, where
f sxd − x 3 2 2x.
(b) Find an equation of the tangent line to the curve
y − x 3 2 2x at the point (2, 4).
(c) Illustrate part (b) by graphing the curve and the tangent
;
line on the same screen.
;
42x
31x
and use them to sketch the graph.
(b) Use your graph from part (a) to sketch the graph of f 9.
(c) Use the definition of a derivative to find f 9sxd.
(d) Graph f 9 and compare with your sketch in part (b).
49. The graph of f is shown. State, with reasons, the numbers
at which f is not differentiable.
y
40. Find a function f and a number a such that
s2 1 hd6 2 64
− f 9sad
h l0
h
lim
_1 0
41. The total cost of repaying a student loan at an interest rate
of r % per year is C − f srd.
(a) What is the meaning of the derivative f 9srd? What are
its units?
(b) What does the statement f 9s10d − 1200 mean?
(c) Is f 9srd always positive or does it change sign?
y
43.
y
y
x
0
6
x
a
b
0
0
4
50. The figure shows the graphs of f , f 9, and f 0. Identify each
curve, and explain your choices.
42–44 Trace or copy the graph of the function. Then sketch a
graph of its derivative directly beneath.
42.
2
x
c
x
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170
CHAPTER 2
Limits and Derivatives
51. Sketch the graph of a function f that satisfies all of the
following conditions:
The domain of f is all real numbers except 0,
lim2 f sxd − 1, lim1 f sxd − 0,
xl0
xl 0
f 9sxd . 0 for all x in the domain of f ,
lim f 9sxd − 0, lim f 9sxd − 1
x l 2`
xl`
52. Let Pstd be the percentage of Americans under the age of 18
at time t. The table gives values of this function in census
years from 1950 to 2010.
54. The total fertility rate at time t, denoted by Fstd, is an estimate of the average number of children born to each woman
(assuming that current birth rates remain constant). The
graph of the total fertility rate in the United States shows
the fluctuations from 1940 to 2010.
(a) Estimate the values of F9s1950d, F9s1965d,
and F9s1987d.
(b) What are the meanings of these derivatives?
(c) Can you suggest reasons for the values of these
derivatives?
t
Pstd
t
Pstd
y
1950
1960
1970
1980
31.1
35.7
34.0
28.0
1990
2000
2010
25.7
25.7
24.0
3.5
3.0
2.5
(a) What is the meaning of P9std? What are its units?
(b) Construct a table of estimated values for P9std.
(c) Graph P and P9.
(d) How would it be possible to get more accurate values
for P9std?
53. Let Bstd be the number of US $20 bills in circulation at time t.
The table gives values of this function from 1995 to 2015, as
of December 31, in billions. Interpret and estimate the value
of B9s2010d.
t
1995
2000
2005
2010
2015
Bstd
4.21
4.93
5.77
6.53
8.57
baby
boom
2.0
baby
bust
baby
boomlet
y=F(t)
1.5
1940
1950
1960
|
1970
1980
1990
2000
2010 t
|
55. Suppose that f sxd < tsxd for all x, where lim x l a tsxd − 0.
Find lim x l a f sxd.
56. Let f sxd − v x b 1 v 2x b .
(a) For what values of a does lim x l a f sxd exist?
(b) At what numbers is f discontinuous?
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Problems Plus
In the Principles of Problem Solving following Chapter 1 we considered the problemsolving strategy of introducing something extra. In the following example we show how
this principle is sometimes useful when we evaluate limits. The idea is to change the
variable — to introduce a new variable that is related to the original variable —in such a
way as to make the problem simpler. Later, in Section 5.5, we will make more extensive
use of this general idea.
3
1 1 cx 2 1
s
, where c is a constant.
xl0
x
EXAMPLE Evaluate lim
SOLUTION As it stands, this limit looks challenging. In Section 2.3 we evaluated limits
in which both numerator and denominator approached 0. There our strategy was to
perform some sort of algebraic manipulation that led to a simplifying cancellation, but
here it’s not clear what kind of algebra is necessary.
So we introduce a new variable t by the equation
3
t−s
1 1 cx
We also need to express x in terms of t, so we solve this equation:
t 3 − 1 1 cx
x−
t3 2 1
c
sif c ± 0d
Notice that x l 0 is equivalent to t l 1. This allows us to convert the given limit into
one involving the variable t :
3
1 1 cx 2 1
t21
s
− lim 3
t l1 st 2 1dyc
xl0
x
lim
− lim
t l1
cst 2 1d
t3 2 1
The change of variable allowed us to replace a relatively complicated limit by a simpler
one of a type that we have seen before. Factoring the denominator as a difference of
cubes, we get
lim
t l1
cst 2 1d
cst 2 1d
− lim
t l1 st 2 1dst 2 1 t 1 1d
t3 2 1
− lim
c
t l1 t 2 1 t 1 1
−
c
3
In making the change of variable we had to rule out the case c − 0. But if c − 0, the
function is 0 for all nonzero x and so its limit is 0. Therefore, in all cases, the limit
is cy3.
n
The following problems are meant to test and challenge your problem-solving skills.
Some of them require a considerable amount of time to think through, so don’t be discouraged if you can’t solve them right away. If you get stuck, you might find it helpful to
refer to the discussion of the principles of problem solving following Chapter 1.
Problems
3
x 21
s
.
x l 1 sx 2 1
1. Evaluate lim
2. Find numbers a and b such that lim
x l0
3. Evaluate lim
xl0
sax 1 b 2 2
− 1.
x
| 2x 2 1 | 2 | 2x 1 1 | .
x
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171
y
4. The figure shows a point P on the parabola y − x 2 and the point Q where the perpendicular
bisector of OP intersects the y-axis. As P approaches the origin along the parabola, what
happens to Q? Does it have a limiting position? If so, find it.
y=≈
Q
P
5. Evaluate the following limits, if they exist, where v x b denotes the greatest integer function.
(a) lim
xl0
0
x
FIGURE FOR PROBLEM 4
v xb
x
(b) lim x v 1yx b
xl0
6. Sketch the region in the plane defined by each of the following equations.
(a) v xb 2 1 v yb 2 − 1
(b) v xb 2 2 v yb 2 − 3
(c) v x 1 yb 2 − 1
(d) v xb 1 v yb − 1
7. Let f sxd − xyv xb .
(b) Evaluate lim x l ` f sxd.
(a) Find the domain and range of f .
8. A fixed point of a function f is a number c in its domain such that f scd − c. (The function
doesn’t move c; it stays fixed.)
(a) Sketch the graph of a continuous function with domain f0, 1g whose range also lies
in f0, 1g. Locate a fixed point of f .
(b) Try to draw the graph of a continuous function with domain f0, 1g and range in f0, 1g
that does not have a fixed point. What is the obstacle?
(c) Use the Intermediate Value Theorem to prove that any continuous function with domain
f0, 1g and range in f0, 1g must have a fixed point.
9. If lim x l a f f sxd 1 tsxdg − 2 and lim x l a f f sxd 2 tsxdg − 1, find lim x l a f f sxd tsxdg.
A
|
P
B
M
FIGURE FOR PROBLEM 10
10. (a) The figure shows an isosceles triangle ABC with /B − /C. The bisector of angle B
intersects the side AC at the point P. Suppose that the base BC remains fixed but the
altitude AM of the triangle approaches 0, so A approaches the midpoint M of BC.
What happens to P during this process? Does it have a limiting position? If so, find it.
(b) Try to sketch the path traced out by P during this process. Then find an equation of this
curve and use this equation to sketch the curve.
C
|
11. (a) If we start from 0° latitude and proceed in a westerly direction, we can let Tsxd denote
the temperature at the point x at any given time. Assuming that T is a continuous
function of x, show that at any fixed time there are at least two diametrically opposite
points on the equator that have exactly the same temperature.
(b) Does the result in part (a) hold for points lying on any circle on the earth’s surface?
(c) Does the result in part (a) hold for barometric pressure and for altitude above sea level?
12. If f is a differentiable function and tsxd − x f sxd, use the definition of a derivative to show
that t9sxd − x f 9sxd 1 f sxd.
13. Suppose f is a function that satisfies the equation
f sx 1 yd − f sxd 1 f s yd 1 x 2 y 1 xy 2
for all real numbers x and y. Suppose also that
lim
x l0
(a) Find f s0d.
(b) Find f 9s0d.
f sxd
−1
x
(c) Find f 9sxd.
|
|
14. Suppose f is a function with the property that f sxd < x 2 for all x. Show that f s0d − 0.
Then show that f 9s0d − 0.
172
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In the project following Section 3.4 you will calculate the distance from an airport runway at which a pilot should start descent for a
smooth landing.
Who is Danny / Shutterstock.com
3
Differentiation Rules
WE HAVE SEEN HOW TO INTERPRET derivatives as slopes and rates of change. We have used the
definition of a derivative to calculate the derivatives of functions defined by formulas. But it would
be tedious if we always had to use the definition, so in this chapter we develop rules for finding
derivatives without having to use the definition directly. These differentiation rules enable us to
calculate with relative ease the derivatives of polynomials, rational functions, algebraic functions,
exponential and logarithmic functions, and trigonometric and inverse trigonometric functions. We
then use these rules to solve problems involving rates of change and the approximation of functions.
173
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
174
CHAPTER 3
Differentiation Rules
3.1 Derivatives of Polynomials and Exponential Functions
In this section we learn how to differentiate constant functions, power functions, polynomials, and exponential functions.
■ Constant Functions
y
Let’s start with the simplest of all functions, the constant function f sxd − c. The graph of
this function is the horizontal line y − c, which has slope 0, so we must have f 9sxd − 0.
(See Figure 1.) A formal proof, from the definition of a derivative, is also easy:
y=c
c
slope=0
f 9sxd − lim
hl0
x
0
f sx 1 hd 2 f sxd
c2c
− lim
− lim 0 − 0
hl0
hl0
h
h
In Leibniz notation, we write this rule as follows.
FIGURE 1
The graph of f sxd − c is the line
y − c, so f 9sxd − 0.
Derivative of a Constant Function
d
scd − 0
dx
■ Power Functions
We next look at the functions f sxd − x n, where n is a positive integer. If n − 1, the graph
of f sxd − x is the line y − x, which has slope 1. (See Figure 2.) So
y
y=x
0
d
sxd − 1
dx
1
slope=1
x
FIGURE 2
The graph of f sxd − x is the line
y − x, so f 9sxd − 1.
(You can also verify Equation 1 from the definition of a derivative.) We have already
investigated the cases n − 2 and n − 3. In fact, in Section 2.8 (Exercises 19 and 20) we
found that
2
d
sx 2 d − 2x
dx
d
sx 3 d − 3x 2
dx
For n − 4 we find the derivative of f sxd − x 4 as follows:
f sx 1 hd 2 f sxd
sx 1 hd4 2 x 4
− lim
hl0
hl0
h
h
f 9sxd − lim
x 4 1 4x 3h 1 6x 2h 2 1 4xh 3 1 h 4 2 x 4
hl0
h
3
2 2
4x h 1 6x h 1 4xh 3 1 h 4
− lim
hl0
h
− lim
− lim s4x 3 1 6x 2h 1 4xh 2 1 h 3 d − 4x 3
hl0
Thus
3
d
sx 4 d − 4x 3
dx
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.1
Derivatives of Polynomials and Exponential Functions
175
Comparing the equations in (1), (2), and (3), we see a pattern emerging. It seems to be a
reasonable guess that, when n is a positive integer, sdydxdsx n d − nx n21. This turns out to
be true. We prove it in two ways; the second proof uses the Binomial Theorem.
The Power Rule If n is a positive integer, then
d
sx n d − nx n21
dx
FIRST PROOF The formula
x n 2 a n − sx 2 adsx n21 1 x n22a 1 ∙ ∙ ∙ 1 xa n22 1 a n21 d
can be verified simply by multiplying out the right-hand side (or by summing the
second factor as a geometric series). If f sxd − x n, we can use Equation 2.7.5 for f 9sad
and the equation above to write
f 9sad − lim
xla
f sxd 2 f sad
xn 2 an
− lim
xla x 2 a
x2a
− lim sx n21 1 x n22a 1 ∙ ∙ ∙ 1 xa n22 1 a n21 d
xla
− a n21 1 a n22a 1 ∙ ∙ ∙ 1 aa n22 1 a n21
− na n21
SECOND PROOF
f sx 1 hd 2 f sxd
sx 1 hd n 2 x n
− lim
hl0
hl0
h
h
f 9sxd − lim
The Binomial Theorem is given on
Reference Page 1.
In finding the derivative of x 4 we had to expand sx 1 hd4. Here we need to expand
sx 1 hd n and we use the Binomial Theorem to do so:
f 9sxd − lim
F
x n 1 nx n21h 1
h
hl0
nx n21h 1
− lim
hl0
− lim
hl0
G
nsn 2 1d n22 2
x h 1 ∙ ∙ ∙ 1 nxh n21 1 h n 2 x n
2
F
nx n21 1
nsn 2 1d n22 2
x h 1 ∙ ∙ ∙ 1 nxh n21 1 h n
2
h
nsn 2 1d n22
x h 1 ∙ ∙ ∙ 1 nxh n22 1 h n21
2
G
− nx n21
because every term except the first has h as a factor and therefore approaches 0.
We illustrate the Power Rule using various notations in Example 1.
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
n
176
CHAPTER 3
Differentiation Rules
EXAMPLE 1
(a) If f sxd − x 6, then f 9sxd − 6x 5.
(c) If y − t 4, then
(b) If y − x 1000, then y9 − 1000x 999.
dy
− 4t 3.
dt
(d)
d 3
sr d − 3r 2
dr
n
What about power functions with negative integer exponents? In Exercise 69 we ask
you to verify from the definition of a derivative that
d
dx
SD
1
x
1
−2 2
x
We can rewrite this equation as
d
sx 21 d − s21dx 22
dx
and so the Power Rule is true when n − 21. In fact, we will show in the next section
[Exercise 3.2.66(c)] that it holds for all negative integers.
What if the exponent is a fraction? In Example 2.8.3 we found that
d
1
sx −
dx
2 sx
which can be written as
d 1y2
sx d − 12 x21y2
dx
This shows that the Power Rule is true even when the exponent is 12. In fact, we will show
in Section 3.6 that it is true for all real exponents n.
The Power Rule (General Version) If n is any real number, then
d
sx n d − nx n21
dx
EXAMPLE 2 Differentiate:
(a) f sxd −
1
x2
3
(b) y − s
x2
SOLUTION In each case we rewrite the function as a power of x.
(a) Since f sxd − x22, we use the Power Rule with n − 22:
2
y
yª
3
_3
_2
FIGURE 3
3
y−s
x2
f 9sxd −
(b)
d
2
sx 22 d − 22x 2221 − 22x 23 − 2 3
dx
x
dy
d 3 2
d
−
(sx ) − dx
sx 2y3 d − 23 x s2y3d21 − 23 x21y3
dx
dx
n
Figure 3 shows the function y in Example 2(b) and its derivative y9. Notice that y is not
differentiable at 0 (y9 is not defined there). Also observe that the function y is increasing
when y9 is positive and is decreasing when y9 is negative. In Chapter 4 we will prove that,
in general, a function increases when its derivative is positive and decreases when its
derivative is negative.
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SECTION 3.1
Derivatives of Polynomials and Exponential Functions
177
The Power Rule enables us to find tangent lines without having to resort to the definition of a derivative. It also enables us to find normal lines. The normal line to a curve C
at a point P is the line through P that is perpendicular to the tangent line at P. (In the
study of optics, the Law of Reflection involves the angle between a light ray and the
normal line to a lens.)
EXAMPLE 3 Find equations of the tangent line and normal line to the curve y − xsx
at the point s1, 1d. Illustrate by graphing the curve and these lines.
3
SOLUTION The derivative of f sxd − xsx − xx 1y2 − x 3y2 is
f 9sxd − 32 x s3y2d21 − 32 x 1y2 − 32 sx
tangent
So the slope of the tangent line at (1, 1) is f 9s1d − 32. Therefore an equation of the
tangent line is
y 2 1 − 32 sx 2 1d
or
y − 32 x 2 12
normal
_1
3
The normal line is perpendicular to the tangent line, so its slope is the negative reciprocal of 32, that is, 223. Thus an equation of the normal line is
_1
y 2 1 − 2 23 sx 2 1d
FIGURE 4
or
y − 2 23 x 1 53
We graph the curve and its tangent line and normal line in Figure 4.
y − xsx
n
■ New Derivatives from Old
When new functions are formed from old functions by addition, subtraction, or multiplication by a constant, their derivatives can be calculated in terms of derivatives of the old
functions. In particular, the following formula says that the derivative of a constant times
a function is the constant times the derivative of the function.
Geometric Interpretation
of the Constant Multiple Rule
The Constant Multiple Rule If c is a constant and f is a differentiable function,
then
d
d
fcf sxdg − c
f sxd
dx
dx
y
y=2ƒ
PROOF Let tsxd − cf sxd. Then
y=ƒ
0
t9sxd − lim
x
hl0
tsx 1 hd 2 tsxd
cf sx 1 hd 2 cf sxd
− lim
h
l
0
h
h
F
f sx 1 hd 2 f sxd
h
f sx 1 hd 2 f sxd
− c lim
hl0
h
− cf 9sxd
Multiplying by c − 2 stretches the
graph vertically by a factor of 2. All
the rises have been doubled but the
runs stay the same. So the slopes are
also doubled.
− lim c
hl0
G
(by Limit Law 3)
n
EXAMPLE 4
d
d
s3x 4 d − 3
sx 4 d − 3s4x 3 d − 12x 3
dx
dx
d
d
d
(b)
s2xd −
fs21dxg − s21d
sxd − 21s1d − 21
dx
dx
dx
(a)
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n
178
CHAPTER 3
Differentiation Rules
The next rule tells us that the derivative of a sum (or difference) of functions is the
sum (or difference) of the derivatives.
Using prime notation, we can write
the Sum and Difference Rules as
The Sum and Difference Rules If f and t are both differentiable, then
d
d
d
f f sxd 1 tsxdg −
f sxd 1
tsxd
dx
dx
dx
s f 1 td9 − f 9 1 t9
s f 2 td9 − f 9 2 t9
d
d
d
f f sxd 2 tsxdg −
f sxd 2
tsxd
dx
dx
dx
PROOF To prove the Sum Rule, we let Fsxd − f sxd 1 tsxd. Then
F9sxd − lim
hl0
− lim
hl0
− lim
hl0
− lim
hl0
Fsx 1 hd 2 Fsxd
h
f f sx 1 hd 1 tsx 1 hdg 2 f f sxd 1 tsxdg
h
F
f sx 1 hd 2 f sxd
tsx 1 hd 2 tsxd
1
h
h
G
f sx 1 hd 2 f sxd
tsx 1 hd 2 tsxd
1 lim
hl 0
h
h
(by Limit Law 1)
− f 9sxd 1 t9sxd
To prove the Difference Rule, we write f 2 t as f 1 s21dt and apply the Sum Rule
and the Constant Multiple Rule.
n
The Sum Rule can be extended to the sum of any number of functions. For instance,
using this theorem twice, we get
s f 1 t 1 hd9 − fs f 1 td 1 hg9 − s f 1 td9 1 h9 − f 9 1 t9 1 h9
The Constant Multiple Rule, the Sum Rule, and the Difference Rule can be combined
with the Power Rule to differentiate any polynomial, as the following three examples
demonstrate.
EXAMPLE 5
d
sx 8 1 12x 5 2 4x 4 1 10x 3 2 6x 1 5d
dx
−
d
d
d
d
d
d
sx 8 d 1 12
sx 5 d 2 4
sx 4 d 1 10
sx 3 d 2 6
sxd 1
s5d
dx
dx
dx
dx
dx
dx
− 8x 7 1 12s5x 4 d 2 4s4x 3 d 1 10s3x 2 d 2 6s1d 1 0
− 8x 7 1 60x 4 2 16x 3 1 30x 2 2 6
n
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SECTION 3.1
y
Derivatives of Polynomials and Exponential Functions
179
EXAMPLE 6 Find the points on the curve y − x 4 2 6x 2 1 4 where the tangent line is
horizontal.
(0, 4)
SOLUTION Horizontal tangents occur where the derivative is zero. We have
0
{_ œ„
3, _5}
x
dy
d
d
d
−
sx 4 d 2 6
sx 2 d 1
s4d
dx
dx
dx
dx
{œ„
3, _5}
FIGURE 5
The curve y − x 4 2 6x 2 1 4 and its
horizontal tangents
− 4x 3 2 12x 1 0 − 4xsx 2 2 3d
Thus dyydx − 0 if x − 0 or x 2 2 3 − 0, that is, x − 6s3 . So the given curve has
horizontal tangents when x − 0, s3 , and 2s3 . The corresponding points are s0, 4d,
(s3 , 25), and (2s3 , 25). (See Figure 5.)
n
EXAMPLE 7 The equation of motion of a particle is s − 2t 3 2 5t 2 1 3t 1 4, where s
is measured in centimeters and t in seconds. Find the acceleration as a function of time.
What is the acceleration after 2 seconds?
SOLUTION The velocity and acceleration are
vstd −
ds
− 6t 2 2 10t 1 3
dt
astd −
dv
− 12t 2 10
dt
The acceleration after 2 seconds is as2d − 14 cmys2.
n
■ Exponential Functions
Let’s try to compute the derivative of the exponential function f sxd − b x using the definition of a derivative:
f sx 1 hd 2 f sxd
b x1h 2 b x
− lim
hl0
hl0
h
h
f 9sxd − lim
b xb h 2 b x
b x sb h 2 1d
− lim
hl0
hl0
h
h
− lim
The factor b x doesn’t depend on h, so we can take it in front of the limit:
bh 2 1
hl0
h
f 9sxd − b x lim
Notice that the limit is the value of the derivative of f at 0, that is,
bh 2 1
− f 9s0d
hl0
h
lim
Therefore we have shown that if the exponential function f sxd − b x is differentiable at
0, then it is differentiable everywhere and
4
f 9sxd − f 9s0d b x
This equation says that the rate of change of any exponential function is proportional to
the function itself. (The slope is proportional to the height.)
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180
CHAPTER 3
h
0.1
Differentiation Rules
2h 2 1
h
3h 2 1
h
0.71773
1.16123
0.01
0.69556
1.10467
0.001
0.69339
1.09922
0.0001
0.69317
1.09867
0.00001
0.69315
1.09862
Numerical evidence for the existence of f 9s0d is given in the table at the left for the
cases b − 2 and b − 3. (Values are stated correct to four decimal places.) It can be
proved that the limits exist and
2h 2 1
for b − 2, f 9s0d − lim
< 0.693
hl0
h
3h 2 1
< 1.099
hl0
h
for b − 3,
f 9s0d − lim
Thus, from Equation 4 we have
d
s2 x d < s0.693d2 x
dx
5
d
s3 x d < s1.099d3 x
dx
Of all possible choices for the base b in Equation 4, the simplest differentiation formula occurs when f 9s0d − 1. In view of the estimates of f 9s0d for b − 2 and b − 3, it
seems reasonable that there is a number b between 2 and 3 for which f 9s0d − 1. It is
traditional to denote this value by the letter e. (In fact, that is how we introduced e in
Section 1.4.) Thus we have the following definition.
In Exercise 1 we will see that e lies
between 2.7 and 2.8. Later we will be
able to show that, correct to five decimal places,
Definition of the Number e
e is the number such that
eh 2 1
−1
hl0
h
lim
e < 2.71828
Geometrically, this means that of all possible exponential functions y − b x, the function f sxd − e x is the one whose tangent line at (0, 1d has a slope f 9s0d that is exactly 1.
(See Figures 6 and 7.)
y
y
y=3®
{x, e ® } slope=e®
y=2®
y=e ®
1
1
slope=1
y=e ®
0
FIGURE 6
x
0
x
FIGURE 7
If we put b − e and, therefore, f 9s0d − 1 in Equation 4, it becomes the following
important differentiation formula.
Derivative of the Natural Exponential Function
d
se x d − e x
dx
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SECTION 3.1
Derivatives of Polynomials and Exponential Functions
181
Thus the exponential function f sxd − e x has the property that it is its own derivative.
The geometrical significance of this fact is that the slope of a tangent line to the curve
y − e x at a point sx, e x d is equal to the y-coordinate of the point (see Figure 7).
EXAMPLE 8 If f sxd − e x 2 x, find f 9 and f 99. Compare the graphs of f and f 9.
SOLUTION Using the Difference Rule, we have
3
f 9sxd −
f
In Section 2.8 we defined the second derivative as the derivative of f 9, so
fª
_1.5
1.5
_1
f 99sxd −
d
d
d
se x 2 1d −
se x d 2
s1d − e x
dx
dx
dx
The function f and its derivative f 9 are graphed in Figure 8. Notice that f has a horizontal tangent when x − 0; this corresponds to the fact that f 9s0d − 0. Notice also that,
for x . 0, f 9sxd is positive and f is increasing. When x , 0, f 9sxd is negative and f is
decreasing.
n
FIGURE 8
y
EXAMPLE 9 At what point on the curve y − e x is the tangent line parallel to the
3
line y − 2x ?
(ln 2, 2)
2
SOLUTION Since y − e x, we have y9 − e x. Let the x-coordinate of the point in
question be a. Then the slope of the tangent line at that point is e a. This tangent line
will be parallel to the line y − 2x if it has the same slope, that is, 2. Equating slopes,
we get
y=2x
1
y=´
d
d
d
se x 2 xd −
se x d 2
sxd − e x 2 1
dx
dx
dx
0
1
ea − 2
x
a − ln 2
Therefore the required point is sa, e a d − sln 2, 2d. (See Figure 9.)
FIGURE 9
n
3.1 Exercises
1. (a) How is the number e defined?
(b) Use a calculator to estimate the values of the limits
h
lim
hl0
2.7 2 1
h
h
and
lim
hl0
2.8 2 1
h
correct to two decimal places. What can you conclude
about the value of e ?
2. (a) Sketch, by hand, the graph of the function f sxd − e x,
paying particular attention to how the graph crosses the
y-axis. What is the slope of the tangent line at that point?
(b) What types of functions are f sxd − e x and tsxd − x e ?
Compare the differentiation formulas for f and t.
(c) Which of the two functions in part (b) grows more
rapidly when x is large?
3–34 Differentiate the function.
3. tsxd − 4x 1 7
4. tstd − 5t 1 4t 2
5. f sxd − x 75 2 x 1 3
6. tsxd − 74 x 2 2 3x 1 12
7. f std − 22e t
8. Fstd − t 3 1 e 3
9. Wsvd − 1.8v23
10. r szd − z 25 2 z 1y2
11. f sxd − x 3y2 1 x 23
12. V std − t 23y5 1 t 4
13. sstd −
1
1
1 2
t
t
15. y − 2x 1 sx
14. r std −
a
b
2 1 4
t
t
16. hswd − s2 w 2 s2
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182
CHAPTER 3
1
17. tsxd −
sx
Differentiation Rules
4
1s
x
19. f sxd − x 3sx 1 3d
21. y − 3e x 1
4
20. Fstd − s2t 2 3d2
22. SsRd − 4! R 2
sx
3
3x 2 1 x 3
x
23. f sxd −
18. Wstd − st 2 2e t
24. y −
sx 1 x
x2
3r 3y2 1 r 5y2
25. Gsrd −
r
s7
26. Gstd − s5t 1
t
27. jsxd − x 2.4 1 e 2.4
28. ksrd − e r 1 r e
29. Fszd −
A 1 Bz 1 Cz 2
z2
30. Gsqd − s1 1 q 21d 2
31. Dstd −
1 1 16t 2
s4td 3
32. f svd −
33. Pswd −
2w 2 2 w 1 4
sw
3
v 2 2ve v
s
v
34. y − e x11 1 1
35–36 Find dyydx and dyydt.
2
t
x
36. y − 2 1
x
t
3
35. y − tx 1 t x
37–40 Find an equation of the tangent line to the curve at the
given point.
37. y − 2x 3 2 x 2 1 2, s1, 3d
38. y − 2e x 1 x, s0, 2d
39. y − x 1
2
, s2, 3d
x
4
40. y − s
x 2 x, s1, 0d
41–42 Find equations of the tangent line and normal line to the
curve at the given point.
4
x
41. y − x 1 2e ,
s0, 2d
42. y − x
, s1, 1d
3y2
; 43–44 Find an equation of the tangent line to the curve at the
given point. Illustrate by graphing the curve and the tangent line
on the same screen.
2
3
43. y − 3x 2 x ,
s1, 2d
44. y − x 2 sx , s1, 0d
; 45–46 Find f 9sxd. Compare the graphs of f and f 9 and use them
to explain why your answer is reasonable.
45. f sxd − x 4 2 2x 3 1 x 2
46. f sxd − x 5 2 2x 3 1 x 2 1
; 47. (a) Graph the function
f sxd − x 4 2 3x 3 2 6x 2 1 7x 1 30
in the viewing rectangle f23, 5g by f210, 50g.
(b) Using the graph in part (a) to estimate slopes, make
a rough sketch, by hand, of the graph of f 9. (See
Example 2.8.1.)
(c) Calculate f 9sxd and use this expression to graph f 9.
Compare with your sketch in part (b).
; 48. (a) Graph the function tsxd − e 2 3x in the viewing
rectangle f21, 4g by f28, 8g.
(b) Using the graph in part (a) to estimate slopes, make
a rough sketch, by hand, of the graph of t9. (See
Example 2.8.1.)
(c) Calculate t9sxd and use this expression to graph t9.
Compare with your sketch in part (b).
x
2
49–50 Find the first and second derivatives of the function.
3
50. G srd − sr 1 s
r
49. f sxd − 0.001x 5 2 0.02x 3
; 51–52 Find the first and second derivatives of the function.
Check to see that your answers are reasonable by comparing the
graphs of f , f 9, and f 99.
51. f sxd − 2 x 2 5x 3y4
52. f sxd − e x 2 x 3
53. The equation of motion of a particle is s − t 3 2 3t, where
s is in meters and t is in seconds. Find
(a) the velocity and acceleration as functions of t,
(b) the acceleration after 2 s, and
(c) the acceleration when the velocity is 0.
54. The equation of motion of a particle is s − t 4 2 2t 3 1 t 2 2 t,
where s is in meters and t is in seconds.
(a) Find the velocity and acceleration as functions of t.
(b) Find the acceleration after 1 s.
(c) Graph the position, velocity, and acceleration functions
;
on the same screen.
55. Biologists have proposed a cubic polynomial to model the
length L of Alaskan rockfish at age A:
L − 0.0155A 3 2 0.372A 2 1 3.95A 1 1.21
where L is measured in inches and A in years. Calculate
dL
dA
Z
A −12
and interpret your answer.
56. The number of tree species S in a given area A in a forest
reserve has been modeled by the power function
SsAd − 0.882 A 0.842
where A is measured in square meters. Find S9s100d and
interpret your answer.
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SECTION 3.1
57. Boyle’s Law states that when a sample of gas is compressed
at a constant temperature, the pressure P of the gas is
inversely proportional to the volume V of the gas.
(a) Suppose that the pressure of a sample of air that occupies
0.106 m 3 at 25°C is 50 kPa. Write V as a function of P.
(b) Calculate dVydP when P − 50 kPa. What is the
meaning of the derivative? What are its units?
58. Car tires need to be inflated properly because overinflation
or underinflation can cause premature tread wear. The data
in the table show tire life L (in thousands of miles) for a certain type of tire at various pressures P (in lbyin2).
P
26
28
31
35
38
42
45
L
50
66
78
81
74
70
59
(a) Use a calculator or computer to model tire life with a
quadratic function of the pressure.
(b) Use the model to estimate dLydP when P − 30 and
when P − 40. What is the meaning of the derivative?
What are the units? What is the significance of the signs
of the derivatives?
59. Find the points on the curve y − x 3 1 3x 2 2 9x 1 10
where the tangent is horizontal.
60. For what value of x does the graph of f sxd − e 2 2x have
a horizontal tangent?
x
61. Show that the curve y − 2e x 1 3x 1 5x 3 has no tangent
line with slope 2.
62. Find an equation of the line that is both tangent to the curve
y − x 4 1 1 and parallel to the line 32 x 2 y − 15.
63. Find equations for two lines that are both tangent to the
curve y − x 3 2 3x 2 1 3x 2 3 and parallel to the line
3x 2 y − 15.
; 64. At what point on the curve y − 1 1 2e 2 3x is the tangent
line parallel to the line 3x 2 y − 5? Illustrate by graphing
the curve and both lines.
x
65. Find an equation of the normal line to the curve y − sx
that is parallel to the line 2x 1 y − 1.
66. Where does the normal line to the parabola y − x 2 2 1 at
the point s21, 0d intersect the parabola a second time? Illustrate with a sketch.
67. Draw a diagram to show that there are two tangent lines to
the parabola y − x 2 that pass through the point s0, 24d.
Find the coordinates of the points where these tangent lines
intersect the parabola.
68. (a) Find equations of both lines through the point s2, 23d
that are tangent to the parabola y − x 2 1 x.
(b) Show that there is no line through the point s2, 7d that is
tangent to the parabola. Then draw a diagram to see why.
69. Use the definition of a derivative to show that if f sxd − 1yx,
then f 9sxd − 21yx 2. (This proves the Power Rule for the
case n − 21.)
Derivatives of Polynomials and Exponential Functions
183
70. Find the nth derivative of each function by calculating the
first few derivatives and observing the pattern that occurs.
(a) f sxd − x n
(b) f sxd − 1yx
71. Find a second-degree polynomial P such that Ps2d − 5,
P9s2d − 3, and P99s2d − 2.
72. The equation y99 1 y9 2 2y − x 2 is called a differential
equation because it involves an unknown function y and its
derivatives y9 and y99. Find constants A, B, and C such that
the function y − Ax 2 1 Bx 1 C satisfies this equation. (Differential equations will be studied in detail in Chapter 9.)
73. Find a cubic function y − ax 3 1 bx 2 1 cx 1 d whose
graph has horizontal tangents at the points s22, 6d and s2, 0d.
74. Find a parabola with equation y − ax 2 1 bx 1 c that has
slope 4 at x − 1, slope 28 at x − 21, and passes through
the point s2, 15d.
75. Let
f sxd −
H
x 2 1 1 if x , 1
x 1 1 if x > 1
Is f differentiable at 1? Sketch the graphs of f and f 9.
76. At what numbers is the following function t differentiable?
H
2x
if x < 0
tsxd − 2x 2 x 2 if 0 , x , 2
22x
if x > 2
Give a formula for t9 and sketch the graphs of t and t9.
|
77. (a) For what values of x is the function f sxd − x 2 2 9
differentiable? Find a formula for f 9.
(b) Sketch the graphs of f and f 9.
|
| |
|
|
78. Where is the function hsxd − x 2 1 1 x 1 2 differentiable? Give a formula for h9 and sketch the graphs of h and h9.
79. Find the parabola with equation y − ax 2 1 bx whose
tangent line at (1, 1) has equation y − 3x 2 2.
80. Suppose the curve y − x 4 1 ax 3 1 bx 2 1 cx 1 d has a
tangent line when x − 0 with equation y − 2x 1 1 and
a tangent line when x − 1 with equation y − 2 2 3x. Find
the values of a, b, c, and d.
81. For what values of a and b is the line 2x 1 y − b tangent to
the parabola y − ax 2 when x − 2?
82. Find the value of c such that the line y − 32 x 1 6 is tangent
to the curve y − csx .
83. What is the value of c such that the line y − 2x 1 3 is tangent to the parabola y − cx 2 ?
84. The graph of any quadratic function f sxd − ax 2 1 bx 1 c
is a parabola. Prove that the average of the slopes of the tangent lines to the parabola at the endpoints of any interval
f p, qg equals the slope of the tangent line at the midpoint of
the interval.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
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184
CHAPTER 3
Differentiation Rules
85. Let
f sxd −
H
x2
if x < 2
mx 1 b if x . 2
(b) Show that the triangle formed by the tangent line and
the coordinate axes always has the same area, no
matter where P is located on the hyperbola.
y
xy=c
Find the values of m and b that make f differentiable
everywhere.
86. Find numbers a and b such that the given function t is
differentiable at 1.
tsxd −
H
ax 3 2 3x if x < 1
bx 2 1 2 if x . 1
x 1000 2 1
.
xl1
x21
87. Evaluate lim
88. A tangent line is drawn to the hyperbola xy − c at a
point P as shown in the figure.
(a) Show that the midpoint of the line segment cut
from this tangent line by the coordinate axes is P.
APPLIED PROJECT
L¡
P
f
Susana Ortega / Shutterstock.com
Q
L™
P
0
x
89. Draw a diagram showing two perpendicular lines that intersect on the y-axis and are both tangent to the parabola y − x 2.
Where do these lines intersect?
90. Sketch the parabolas y − x 2 and y − x 2 2 2x 1 2. Do you
think there is a line that is tangent to both curves? If so, find
its equation. If not, why not?
91. If c . 12, how many lines through the point s0, cd are normal
lines to the parabola y − x 2 ? What if c < 12 ?
BUILDING A BETTER ROLLER COASTER
Suppose you are asked to design the first ascent and drop for a new roller coaster. By studying photographs of your favorite coasters, you decide to make the slope of the ascent 0.8 and
the slope of the drop 21.6. You decide to connect these two straight stretches y − L 1sxd and
y − L 2 sxd with part of a parabola y − f sxd − a x 2 1 bx 1 c, where x and f sxd are measured
in feet. For the track to be smooth there can’t be abrupt changes in direction, so you want the
linear segments L 1 and L 2 to be tangent to the parabola at the transition points P and Q. (See
the figure.) To simplify the equations, you decide to place the origin at P.
1. (a) Suppose the horizontal distance between P and Q is 100 ft. Write equations in a, b, and
c that will ensure that the track is smooth at the transition points.
(b) Solve the equations in part (a) for a, b, and c to find a formula for f sxd.
; (c) Plot L 1, f , and L 2 to verify graphically that the transitions are smooth.
(d) Find the difference in elevation between P and Q.
2. The solution in Problem 1 might look smooth, but it might not feel smooth because the
piecewise defined function [consisting of L 1sxd for x , 0, f sxd for 0 < x < 100, and L 2sxd
for x . 100] doesn’t have a continuous second derivative. So you decide to improve the
design by using a quadratic function qsxd − ax 2 1 bx 1 c only on the interval
10 < x < 90 and connecting it to the linear functions by means of two cubic functions:
tsxd − kx 3 1 lx 2 1 mx 1 n
0 < x , 10
hsxd − px 3 1 qx 2 1 rx 1 s
90 , x < 100
(a) Write a system of equations in 11 unknowns that ensures that the functions and their
first two derivatives agree at the transition points.
(b) Solve the system of equations in part (a) to find formulas for qsxd, tsxd, and hsxd.
(c) Plot L 1, t, q, h, and L 2, and compare with the plot in Problem 1(c).
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SECTION 3.2
The Product and Quotient Rules
185
3.2 The Product and Quotient Rules
The formulas of this section enable us to differentiate new functions that are formed from
old functions by using multiplication or division.
■ The Product Rule
Î√
u Î√
Îu Î√
√
u√
√ Îu
By analogy with the Sum and Difference Rules, we might be tempted to guess, as Leibniz did three centuries ago, that the derivative of a product is the product of the derivatives. We can see, however, that this guess is wrong by looking at a particular example.
Let f sxd − x and tsxd − x 2. Then the Power Rule gives f 9sxd − 1 and t9sxd − 2x. But
s ftdsxd − x 3, so s ftd9sxd − 3x 2. Thus s ftd9 ± f 9t9. The correct formula was discovered
by Leibniz (soon after his false start) and is called the Product Rule.
Before stating the Product Rule, let’s see how we might discover it. We start by assuming that u − f sxd and v − tsxd are both positive differentiable functions. Then we can
interpret the product uv as an area of a rectangle (see Figure 1). If x changes by an
amount Dx, then the corresponding changes in u and v are
Dv − tsx 1 Dxd 2 tsxd
Du − f sx 1 Dxd 2 f sxd
u
Îu
FIGURE 1
The geometry of the Product Rule
and the new value of the product, su 1 Dudsv 1 Dvd, can be interpreted as the area of the
large rectangle in Figure 1 (provided that Du and Dv happen to be positive).
The change in the area of the rectangle is
1
Dsuvd − su 1 Dudsv 1 Dvd 2 uv − u Dv 1 v Du 1 Du Dv
− the sum of the three shaded areas
If we divide by Dx, we get
Dsuvd
Dv
Du
Dv
−u
1v
1 Du
Dx
Dx
Dx
Dx
If we now let Dx l 0, we get the derivative of uv :
S
d
Dsuvd
Dv
Du
Dv
suvd − lim
− lim u
1v
1 Du
Dx l 0 Dx
Dx l 0
dx
Dx
Dx
Dx
Recall that in Leibniz notation the
definition of a derivative can be
written as
dy
Dy
− lim
Dx l 0 Dx
dx
− u lim
Dv
Dx l 0 Dx
−u
2
1 v lim
Du
Dx l 0 Dx
1
S
DS
lim Du
Dx l 0
lim
D
Dv
Dx l 0 Dx
D
dv
du
dv
1v
10!
dx
dx
dx
d
dv
du
suvd − u
1v
dx
dx
dx
(Notice that Du l 0 as Dx l 0 since f is differentiable and therefore continuous.)
Although we started by assuming (for the geometric interpretation) that all the quantities are positive, we notice that Equation 1 is always true. (The algebra is valid whether
u, v, Du, and Dv are positive or negative.) So we have proved Equation 2, known as the
Product Rule, for all differentiable functions u and v.
In prime notation the Product Rule is
written as
s ftd9 − ft9 1 t f 9
The Product Rule If f and t are both differentiable, then
d
d
d
f f sxd tsxdg − f sxd
ftsxdg 1 tsxd
f f sxdg
dx
dx
dx
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186
CHAPTER 3
Differentiation Rules
In words, the Product Rule says that the derivative of a product of two functions is the
first function times the derivative of the second function plus the second function times
the derivative of the first function.
EXAMPLE 1
(a) If f sxd − xe x, find f 9sxd.
(b) Find the nth derivative, f sndsxd.
Figure 2 shows the graphs of the
function f of Example 1 and its derivative f 9. Notice that f 9sxd is positive
when f is increasing and negative
when f is decreasing.
SOLUTION
(a) By the Product Rule, we have
d
sxe x d
dx
d
d
−x
se x d 1 e x
sxd
dx
dx
f 9sxd −
3
− xe x 1 e x ∙ 1 − sx 1 1de x
f
fª
_3
(b) Using the Product Rule a second time, we get
1.5
_1
FIGURE 2
d
fsx 1 1de x g
dx
d
d
− sx 1 1d
se x d 1 e x
sx 1 1d
dx
dx
f 99sxd −
− sx 1 1de x 1 e x ! 1 − sx 1 2de x
Further applications of the Product Rule give
f 999sxd − sx 1 3de x
f s4dsxd − sx 1 4de x
In fact, each successive differentiation adds another term e x, so
f sndsxd − sx 1 nde x
In Example 2, a and b are constants.
It is customary in mathematics to
use letters near the beginning of the
alphabet to represent constants and
letters near the end of the alphabet to
represent variables.
n
EXAMPLE 2 Differentiate the function f std − st sa 1 btd.
SOLUTION 1 Using the Product Rule, we have
f 9std − st
d
d
sa 1 btd 1 sa 1 btd
(st )
dt
dt
− st ! b 1 sa 1 btd ! 12 t 21y2
− bst 1
a 1 bt
a 1 3bt
−
2 st
2 st
SOLUTION 2 If we first use the laws of exponents to rewrite f std, then we can proceed
directly without using the Product Rule.
f std − ast 1 btst − at 1y2 1 bt 3y2
f 9std − 12 at21y2 1 32 bt 1y2
which is equivalent to the answer given in Solution 1.
n
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SECTION 3.2
The Product and Quotient Rules
187
Example 2 shows that it is sometimes easier to simplify a product of functions before
differentiating than to use the Product Rule. In Example 1, however, the Product Rule is
the only possible method.
EXAMPLE 3 If f sxd − sx tsxd, where ts4d − 2 and t9s4d − 3, find f 9s4d.
SOLUTION Applying the Product Rule, we get
f 9sxd −
d
d
d
ftsxdg 1 tsxd
sx tsxd − sx
sx
dx
dx
dx
f
g
f g
− sx t9sxd 1 tsxd ∙ 12 x 21y2
tsxd
− sx t9sxd 1
2sx
f 9s4d − s4 t9s4d 1
So
ts4d
2s4
−2∙31
2
− 6.5
2∙2
n
■ The Quotient Rule
We find a rule for differentiating the quotient of two differentiable functions u − f sxd
and v − tsxd in much the same way that we found the Product Rule. If x, u, and v change
by amounts Dx, Du, and Dv, then the corresponding change in the quotient uyv is
SD
D
u
v
−
−
d
dx
so
SD
u
v
u 1 Du
u
su 1 Dudv 2 usv 1 Dvd
2 −
v 1 Dv
v
v sv 1 Dvd
v Du 2 u Dv
v sv 1 Dvd
− lim
Dxl0
Dsuyvd
− lim
Dxl0
Dx
v
Du
Dv
2u
Dx
Dx
v sv 1 Dvd
As Dx l 0, Dv l 0 also, because v − tsxd is differentiable and therefore continuous.
Thus, using the Limit Laws, we get
d
dx
In prime notation the Quotient Rule
is written as
SD
f 9
t f 9 2 ft9
−
t
t2
SD
u
v
v lim
−
Du
D x l 0 Dx
2 u lim
Dv
D x l 0 Dx
v lim sv 1 Dvd
v
−
Dxl0
du
dv
2u
dx
dx
v2
The Quotient Rule If f and t are differentiable, then
d
dx
F G
f sxd
tsxd
tsxd
−
d
d
f f sxdg 2 f sxd
ftsxdg
dx
dx
ftsxdg 2
In words, the Quotient Rule says that the derivative of a quotient is the denominator
times the derivative of the numerator minus the numerator times the derivative of the
denominator, all divided by the square of the denominator.
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188
CHAPTER 3
Differentiation Rules
The Quotient Rule and the other differentiation formulas enable us to compute the
derivative of any rational function, as the next example illustrates.
Figure 3 shows the graphs of the
function of Example 4 and its derivative. Notice that when y grows rapidly
3
(near 2s
6 < 21.8), y9 is large. And
when y grows slowly, y9 is near 0.
EXAMPLE 4 Let y −
sx 3 1 6d
y9 −
1.5
yª
_4
4
y
_1.5
FIGURE 3
x2 1 x 2 2
. Then
x3 1 6
d
d
sx 2 1 x 2 2d 2 sx 2 1 x 2 2d
sx 3 1 6d
dx
dx
sx 3 1 6d2
−
sx 3 1 6ds2x 1 1d 2 sx 2 1 x 2 2ds3x 2 d
sx 3 1 6d2
−
s2x 4 1 x 3 1 12x 1 6d 2 s3x 4 1 3x 3 2 6x 2 d
sx 3 1 6d2
−
2x 4 2 2x 3 1 6x 2 1 12x 1 6
sx 3 1 6d2
n
EXAMPLE 5 Find an equation of the tangent line to the curve y − e xys1 1 x 2 d at the
point (1, 12 e).
SOLUTION According to the Quotient Rule, we have
dy
−
dx
2.5
y=
´
1+≈
1
0
FIGURE 4
d
d
se x d 2 e x
s1 1 x 2 d
dx
dx
s1 1 x 2 d2
−
s1 1 x 2 de x 2 e x s2xd
e x s1 2 2x 1 x 2 d
−
s1 1 x 2 d2
s1 1 x 2 d 2
−
e x s1 2 xd2
s1 1 x 2 d2
So the slope of the tangent line at (1, 12 e) is
y=2 e
_2
s1 1 x 2 d
3.5
dy
dx
Z
x−1
−0
This means that the tangent line at (1, 12 e) is horizontal and its equation is y − 12 e. (See
Figure 4.)
n
NOTE Don’t use the Quotient Rule every time you see a quotient. Sometimes it’s easier
to rewrite a quotient first to put it in a form that is simpler for the purpose of differentiation. For instance, although it is possible to differentiate the function
Fsxd −
3x 2 1 2sx
x
using the Quotient Rule, it is much easier to perform the division first and write the function as
Fsxd − 3x 1 2x 21y2
before differentiating.
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SECTION 3.2
The Product and Quotient Rules
189
We summarize the differentiation formulas we have learned so far as follows.
Table of Differentiation Formulas
d
scd − 0
dx
d n
sx d − nx n21
dx
d x
se d − e x
dx
scf d9 − cf 9
s f 1 td9 − f 9 1 t9
s f 2 td9 − f 9 2 t9
s ftd9 − ft9 1 tf 9
SD
f 9
tf 9 2 ft9
−
t
t2
3.2 Exercises
1. Find the derivative of f sxd − s1 1 2x 2 dsx 2 x 2 d in two
ways: by using the Product Rule and by performing the multiplication first. Do your answers agree?
2. Find the derivative of the function
x 2 5x 1 sx
x2
4
Fsxd −
3
in two ways: by using the Quotient Rule and by simplifying
first. Show that your answers are equivalent. Which method
do you prefer?
20. f szd − s1 2 e z dsz 1 e z d
21. Vstd − st 1 2e t d st
22. Wstd − e t s1 1 te t d
23. y − e p ( p 1 p sp )
24. hsrd −
25. f std −
3
t
s
t23
26. y − sz 2 1 e z dsz
27. f sxd −
x 2e x
x 1 ex
28. Fstd −
At
Bt 2 1 Ct 3
30. f sxd −
ax 1 b
cx 1 d
3–30 Differentiate.
3. y − s4x 2 1 3ds2x 1 5d
29. f sxd −
4. y − s10x 2 1 7x 2 2ds2 2 x 2 d
5. y − x 3 e x
6. y − se x 1 2ds2e x 2 1d
7. f sxd − s3x 2 2 5xde x
8. tsxd − ( x 1 2sx ) e x
x
9. y − x
e
ex
10. y −
1 2 ex
11. tstd −
3 2 2t
5t 1 1
12. Gsud −
6u 4 2 5u
u11
13. f std −
5t
t3 2 t 2 1
14. Fsxd −
1
2x 3 2 6x 2 1 5
s 2 ss
15. y −
s2
17. Jsud −
S
1
1
1 2
u
u
16. y −
DS D
u1
1
u
18. hswd − sw 2 1 3wdsw 21 2 w 24 d
19. Hsud − (u 2 su )(u 1 su )
sx
ae r
b 1 er
2
x
c
x1
x
31–34 Find f 9sxd and f 99sxd.
32. f sxd − sx e x
31. f sxd − x 2e x
33. f sxd −
x
x2 2 1
34. f sxd −
x
1 1 sx
35–36 Find an equation of the tangent line to the given curve at
the specified point.
35. y −
x2
,
11x
(1, 12 )
36. y −
11x
,
1 1 ex
(0, 12 )
sx 1 1
37–38 Find equations of the tangent line and normal line to the
given curve at the specified point.
37. y −
3x
,
1 1 5x 2
(1, 12 )
38. y − x 1 xe x, s0, 0d
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190
CHAPTER 3
Differentiation Rules
39. (a) The curve y − 1ys1 1 x 2 d is called a witch of Maria
Agnesi. Find an equation of the tangent line to this
curve at the point (21, 12 ).
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on the same screen.
52. Let Psxd − FsxdGsxd and Qsxd − FsxdyGsxd, where F and
G are the functions whose graphs are shown.
(a) Find P9s2d.
(b) Find Q9s7d.
y
F
40. (a) The curve y − xys1 1 x 2 d is called a serpentine. Find
an equation of the tangent line to this curve at the
point s3, 0.3d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on the same screen.
41. (a) If f sxd − sx 3 2 xde x, find f 9sxd.
(b) Check to see that your answer to part (a) is reasonable
;
by comparing the graphs of f and f 9.
;
42. (a) If f sxd − sx 2 2 1dysx 2 1 1d, find f 9sxd and f 99sxd.
(b) Check to see that your answers to part (a) are reasonable by comparing the graphs of f , f 9, and f 99.
43. If f sxd − x 2ys1 1 xd, find f 99s1d.
44. If tsxd − xye x, find t sndsxd.
45. Suppose that f s5d − 1, f 9s5d − 6, ts5d − 23, and
t9s5d − 2. Find the following values.
(a) s ftd9s5d
(b) s fytd9s5d
(c) s tyf d9s5d
46. Suppose that f s4d − 2, ts4d − 5, f 9s4d − 6, and
t9s4d − 23. Find h9s4d.
(a) hsxd − 3 f sxd 1 8tsxd
(b) hsxd − f sxdtsxd
tsxd
(d) hsxd −
f sxd 1 tsxd
f sxd
(c) hsxd −
tsxd
47. If f sxd − e x tsxd, where ts0d − 2 and t9s0d − 5, find f 9s0d.
G
1
0
1
x
53. If t is a differentiable function, find an expression for the
derivative of each of the following functions.
x
(a) y − x tsxd
(b) y −
tsxd
tsxd
(c) y −
x
54. If f is a differentiable function, find an expression for the
derivative of each of the following functions.
f sxd
(a) y − x 2 f sxd
(b) y −
x2
(c) y −
x2
f sxd
(d) y −
S DZ
hsxd
x
56. Find equations of the tangent lines to the curve
y−
50. If f s2d − 10 and f 9sxd − x 2 f sxd for all x, find f 99s2d.
51. If f and t are the functions whose graphs are shown, let
usxd − f sxdtsxd and vsxd − f sxdytsxd.
(a) Find u9s1d.
(b) Find v9s4d.
y
57. Find R9s0d, where
Rsxd −
x 2 3x 3 1 5x 5
1 1 3x 3 1 6x 6 1 9x 9
Hint: Instead of finding R9sxd first, let f sxd be the numerator and tsxd be the denominator of Rsxd, and compute R9s0d
from f s0d, f 9s0d, ts0d, and t9s0d.
58. Use the method of Exercise 57 to compute Q9s0d, where
Qsxd −
f
0
g
1
x21
x11
that are parallel to the line x 2 2y − 2.
x−2
49. If tsxd − x f sxd, where f s3d − 4 and f 9s3d − 22, find an
equation of the tangent line to the graph of t at the point
where x − 3.
1
sx
55. How many tangent lines to the curve y − xysx 1 1) pass
through the point s1, 2d? At which points do these tangent
lines touch the curve?
48. If hs2d − 4 and h9s2d − 23, find
d
dx
1 1 x f sxd
x
1 1 x 1 x 2 1 xe x
1 2 x 1 x 2 2 xe x
59. In this exercise we estimate the rate at which the total personal income is rising in Boulder, Colorado. In 2015, the
population of this city was 107,350 and the population was
increasing by roughly 1960 people per year. The average
annual income was $60,220 per capita, and this average
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SECTION 3.3
was increasing at about $2250 per year (a little above the
national average of about $1810 yearly). Use the Product
Rule and these figures to estimate the rate at which total
personal income was rising in Boulder in 2015. Explain the
meaning of each term in the Product Rule.
60. A manufacturer produces bolts of a fabric with a fixed width.
The quantity q of this fabric (measured in yards) that is sold
is a function of the selling price p (in dollars per yard), so we
can write q − f s pd. Then the total revenue earned with selling price p is Rs pd − pf s pd.
(a) What does it mean to say that f s20d − 10,000 and
f 9s20d − 2350?
(b) Assuming the values in part (a), find R9s20d and interpret
your answer.
61. The Michaelis-Menten equation for the enzyme chymotrypsin is
v−
0.14fSg
0.015 1 fSg
Derivatives of Trigonometric Functions
191
63. Extended Product Rule The Product Rule can be extended to
the product of three functions.
(a) Use the Product Rule twice to prove that if f , t, and h are
differentiable, then s fthd9 − f 9th 1 ft9h 1 fth9.
(b) Taking f − t − h in part (a), show that
d
f f sxdg 3 − 3f f sxdg 2 f 9sxd
dx
(c) Use part (b) to differentiate y − e 3x.
64. (a) If Fsxd − f sxd tsxd, where f and t have derivatives of all
orders, show that F99 − f 99t 1 2 f 9t9 1 f t99.
(b) Find similar formulas for F999 and F s4d.
(c) Guess a formula for F snd.
65. Find expressions for the first five derivatives of f sxd − x 2e x.
Do you see a pattern in these expressions? Guess a formula
for f sndsxd and prove it using mathematical induction.
66. Reciprocal Rule If t is differentiable, the Reciprocal Rule
says that
where v is the rate of an enzymatic reaction and [S] is the
concentration of a substrate S. Calculate d vyd fSg and interpret it.
62. The biomass Bstd of a fish population is the total mass of the
members of the population at time t. It is the product of the
number of individuals Nstd in the population and the average
mass Mstd of a fish at time t. In the case of guppies, breeding
occurs continually. Suppose that at time t − 4 weeks the population is 820 guppies and is growing at a rate of 50 guppies
per week, while the average mass is 1.2 g and is increasing at
a rate of 0.14 gyweek. At what rate is the biomass increasing
when t − 4?
d
dx
F G
1
tsxd
−2
t9sxd
f tsxdg 2
(a) Use the Quotient Rule to prove the Reciprocal Rule.
(b) Use the Reciprocal Rule to differentiate the function in
Exercise 14.
(c) Use the Reciprocal Rule to verify that the Power Rule is
valid for negative integers, that is,
d
sx 2n d − 2nx2n21
dx
for all positive integers n.
3.3 Derivatives of Trigonometric Functions
A review of the trigonometric functions is given in Appendix D.
Before starting this section, you might need to review the trigonometric functions. In
particular, it is important to remember that when we talk about the function f defined for
all real numbers x by
f sxd − sin x
it is understood that sin x means the sine of the angle whose radian measure is x. A similar convention holds for the other trigonometric functions cos, tan, csc, sec, and cot.
Recall from Section 2.5 that all of the trigonometric functions are continuous at every
number in their domains.
■ Derivatives of the Trigonometric Functions
If we sketch the graph of the function f sxd − sin x and use the interpretation of f 9sxd
as the slope of the tangent to the sine curve in order to sketch the graph of f 9 (see
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192
CHAPTER 3
Differentiation Rules
Exercise 2.8.16), then it looks as if the graph of f 9 may be the same as the cosine
curve (see Figure 1).
y
y=ƒ=sin x
0
π
2
π
2π
x
y
y=fª(x )
0
π
2
π
x
FIGURE 1
Let’s try to confirm our guess that if f sxd − sin x, then f 9sxd − cos x. From the definition of a derivative, we have
f sx 1 hd 2 f sxd
hl0
h
f 9sxd − lim
− lim
hl0
sinsx 1 hd 2 sin x
h
sin x cos h 1 cos x sin h 2 sin x
hl0
h
− lim
− lim
hl0
− lim
hl0
1
F
F S
(using the addition formula for
sine; see Appendix D)
G
S DG
sin x cos h 2 sin x
cos x sin h
1
h
h
sin x
cos h 2 1
h
− lim sin x ! lim
hl0
hl0
D
1 cos x
sin h
h
cos h 2 1
sin h
1 lim cos x ! lim
hl0
hl0
h
h
Two of these four limits are easy to evaluate. Because we regard x as a constant when
computing a limit as h l 0, we have
lim sin x − sin x
hl0
and
lim cos x − cos x
hl0
Later in this section we will prove that
lim
hl0
sin h
−1
h
and
lim
hl0
cos h 2 1
−0
h
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SECTION 3.3
Derivatives of Trigonometric Functions
193
Putting these limits into (1), we get
f 9sxd − lim sin x ! lim
hl0
hl0
cos h 2 1
sin h
1 lim cos x ! lim
h
l
0
h
l
0
h
h
− ssin xd ! 0 1 scos xd ! 1 − cos x
So we have proved the formula for the derivative of the sine function:
d
ssin xd − cos x
dx
2
EXAMPLE 1 Differentiate y − x 2 sin x.
Figure 2 shows the graphs of the
function of Example 1 and its derivative. Notice that y9 − 0 whenever y
has a horizontal tangent.
SOLUTION Using the Product Rule and Formula 2, we have
dy
d
d
− x2
ssin xd 1 sin x
sx 2 d
dx
dx
dx
5
− x 2 cos x 1 2x sin x
yª
_4
y
4
Using the same methods as in the proof of Formula 2, we can prove (see Exercise 26)
that
d
scos xd − 2sin x
dx
3
_5
FIGURE 2
n
The tangent function can also be differentiated by using the definition of a derivative,
but it is easier to use the Quotient Rule together with Formulas 2 and 3:
d
d
stan xd −
dx
dx
S D
cos x
−
4
sin x
cos x
d
d
ssin xd 2 sin x
scos xd
dx
dx
cos2x
−
cos x ! cos x 2 sin x s2sin xd
cos2x
−
cos2x 1 sin2x
cos2x
−
1
− sec2x
cos2x
scos2x 1 sin2x − 1d
d
stan xd − sec2x
dx
The derivatives of the remaining trigonometric functions, csc, sec, and cot, can
also be found easily using the Quotient Rule (see Exercises 23 –25). We collect all the
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194
CHAPTER 3
Differentiation Rules
differentiation formulas for trigonometric functions in the following table. Remember
that they are valid only when x is measured in radians.
Derivatives of Trigonometric Functions
When you memorize this table, it
is helpful to notice that the minus
signs go with the derivatives of the
“cofunctions,” that is, cosine,
cosecant, and cotangent.
d
ssin xd − cos x
dx
d
scos xd − 2sin x
dx
d
stan xd − sec2x
dx
d
scsc xd − 2csc x cot x
dx
d
ssec xd − sec x tan x
dx
d
scot xd − 2csc 2x
dx
EXAMPLE 2 Differentiate f sxd −
of f have a horizontal tangent?
sec x
. For what values of x does the graph
1 1 tan x
SOLUTION The Quotient Rule gives
s1 1 tan xd
f 9sxd −
3
_π
π
2π
_3
FIGURE 3
The horizontal tangents in Example 2
d
d
ssec xd 2 sec x
s1 1 tan xd
dx
dx
s1 1 tan xd2
−
s1 1 tan xd sec x tan x 2 sec x ! sec2x
s1 1 tan xd2
−
sec x stan x 1 tan2x 2 sec2xd
s1 1 tan xd2
−
sec x stan x 2 1d
s1 1 tan xd2
ssec2 x − tan2 x 1 1d
Because sec x is never 0, we see that f 9sxd − 0 when tan x − 1, and this occurs
when x − !y4 1 n! , where n is an integer (see Figure 3).
n
Trigonometric functions are often used in modeling real-world phenomena. In particular, vibrations, waves, elastic motions, and other quantities that vary in a periodic
manner can be described using trigonometric functions. In the following example we
discuss an instance of simple harmonic motion.
_4
0
4
s
FIGURE 4
EXAMPLE 3 An object fastened to the end of a vertical spring is stretched 4 cm
beyond its rest position and released at time t − 0. (See Figure 4 and note that the
downward direction is positive.) Its position at time t is
s − f std − 4 cos t
Find the velocity and acceleration at time t and use them to analyze the motion of the object.
SOLUTION The velocity and acceleration are
ds
d
d
−
s4 cos td − 4
scos td − 24 sin t
dt
dt
dt
dv
d
d
a−
−
s24 sin td − 24
ssin td − 24 cos t
dt
dt
dt
v−
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SECTION 3.3
4
s
√
a
0
2π t
_4
195
The object oscillates from the lowest point ss − 4 cmd to the highest point
ss − 24 cmd. The period of the oscillation is 2!, the period of cos t.
The speed is v − 4 sin t , which is greatest when sin t − 1, that is, when
cos t − 0. So the object moves fastest as it passes through its equilibrium position
ss − 0d. Its speed is 0 when sin t − 0, that is, at the highest and lowest points.
The acceleration a − 24 cos t − 0 when s − 0. It has greatest magnitude at the
highest and lowest points. See the graphs in Figure 5.
n
| |
π
Derivatives of Trigonometric Functions
|
|
|
|
EXAMPLE 4 Find the 27th derivative of cos x.
SOLUTION The first few derivatives of f sxd − cos x are as follows:
FIGURE 5
f 9sxd − 2sin x
f 0sxd − 2cos x
f -sxd − sin x
f s4dsxd − cos x
PS
f s5dsxd − 2sin x
Look for a pattern.
We see that the successive derivatives occur in a cycle of length 4 and, in particular,
f sndsxd − cos x whenever n is a multiple of 4. Therefore
f s24dsxd − cos x
and, differentiating three more times, we have
f s27dsxd − sin x
n
■ Two Special Trigonometric Limits
D
5
B
1
O
In proving the formula for the derivative of sine we used two special limits, which we
now prove.
E
¨
C
A
lim
"l0
PROOF Assume first that " lies between 0 and !y2. Figure 6(a) shows a sector of a circle with center O, central angle ", and radius 1. BC is drawn perpendicular to OA. By the definition of radian measure, we have arc AB − ". Also
BC − OB sin " − sin ". From the diagram we see that
| | |
|
| BC | , | AB | , arc AB
(a)
Therefore
B
E
A
O
sin "
−1
"
sin " , "
so
sin "
,1
"
Let the tangent lines at A and B intersect at E. You can see from Figure 6(b) that the
circumference of a circle is smaller than the length of a circumscribed polygon, and
so arc AB , AE 1 EB . Thus
| | | |
| | | |
| | | |
− | AD | − | OA | tan "
" − arc AB , AE 1 EB
, AE 1 ED
(b)
FIGURE 6
− tan "
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196
CHAPTER 3
Differentiation Rules
(In Appendix F the inequality " < tan " is proved directly from the definition of the
length of an arc without resorting to geometric intuition as we did here.) Therefore
we have
",
so
cos " ,
sin "
cos "
sin "
,1
"
We know that lim " l 0 1 − 1 and lim " l 0 cos " − 1, so by the Squeeze Theorem, we
have
sin "
−1
"
lim
"l 01
s0 , " , !y2d
But the function ssin "dy" is an even function, so its right and left limits must be equal.
Hence, we have
lim
"l0
sin "
−1
"
so we have proved Equation 5.
n
The first special limit we considered concerned the sine function. The following special limit involves cosine.
6
lim
"l0
cos " 2 1
−0
"
PROOF We multiply numerator and denominator by cos " 1 1 in order to put the
function in a form in which we can use limits that we know.
cos " 2 1
− lim
"l0
"l0
"
lim
S
D
S
cos " 2 1 cos " 1 1
!
"
cos " 1 1
2sin 2"
− 2lim
" l 0 " scos " 1 1d
"l0
− lim
cos2" 2 1
" l 0 " scos " 1 1d
− lim
sin "
sin "
!
"
cos " 1 1
D
sin "
sin "
! lim
"l0
" l 0 cos " 1 1
"
− 2lim
− 21 !
S D
0
111
−0
(by Equation 5)
n
sin 7x
.
xl0
4x
EXAMPLE 5 Find lim
SOLUTION In order to apply Equation 5, we first rewrite the function by multiplying
and dividing by 7:
Note that sin 7x ± 7 sin x.
sin 7x
7
−
4x
4
S D
sin 7x
7x
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SECTION 3.3
Derivatives of Trigonometric Functions
197
If we let " − 7x, then " l 0 as x l 0, so by Equation 5 we have
lim
xl0
S D
sin 7x
7
sin 7x
− lim
x
l
0
4x
4
7x
7
sin "
7
7
lim
− !1−
"
l
0
4
"
4
4
−
n
EXAMPLE 6 Calculate lim x cot x.
xl0
SOLUTION Here we divide numerator and denominator by x:
lim x cot x − lim
xl0
xl0
x cos x
sin x
lim cos x
xl0
cos x
− lim
−
sin x
x l 0 sin x
lim
xl0
x
x
−
cos 0
1
(by the continuity of cosine and Equation 5)
−1
n
cos " 2 1
.
"l0
sin "
EXAMPLE 7 Find lim
SOLUTION In order to use Equations 5 and 6 we divide numerator and denominator by ":
cos " 2 1
lim
− lim
"l0
"l0
sin "
cos " 2 1
"
sin "
"
cos " 2 1
"
0
− −0
sin "
1
lim
"l0
"
lim
−
"l0
n
3.3 Exercises
1–22 Differentiate.
13. f s"d −
1. f sxd − 3 sin x 2 2 cos x
2. f sxd − tan x 2 4 sin x
3. y − x 2 1 cot x
4. y − 2 sec x 2 csc x
15. y −
5. hs"d − " 2 sin "
6. tsxd − 3x 1 x 2 cos x
17. f swd −
7. y − sec " tan "
8. y − sin " cos "
9. f s"d − s" 2 cos "d sin "
10. ts"d − e stan " 2 "d
11. Hstd − cos 2 t
12. f sxd − e x sin x 1 cos x
"
19. y −
sin "
1 1 cos "
x
2 2 tan x
1 1 sec w
1 2 sec w
t sin t
11t
21. f s"d − " cos " sin "
14. y −
cos x
1 2 sin x
16. f std −
18. y −
cot t
et
sin t
1 1 tan t
20. tszd −
z
sec z 1 tan z
22. f std − te t cot t
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198
CHAPTER 3
Differentiation Rules
23. Show that
d
scsc xd − 2csc x cot x.
dx
24. Show that
d
ssec xd − sec x tan x.
dx
25. Show that
d
scot xd − 2csc 2x.
dx
41. A mass on a spring vibrates horizontally on a smooth
level surface (see the figure). Its equation of motion is
xstd − 8 sin t, where t is in seconds and x in centimeters.
(a) Find the velocity and acceleration at time t.
(b) Find the position, velocity, and acceleration of the mass
at time t − 2!y3. In what direction is it moving at that
time?
26. Prove, using the definition of a derivative, that if
f sxd − cos x, then f 9sxd − 2sin x.
equilibrium
position
27–30 Find an equation of the tangent line to the curve at the
given point.
27. y − sin x 1 cos x, s0, 1d
0
28. y − x 1 sin x, s!, !d
29. y − e x cos x 1 sin x, s0, 1d
1 1 sin x
30. y −
, s!, 21d
cos x
31. (a) Find an equation of the tangent line to the curve
y − 2x sin x at the point s!y2, !d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on the same screen.
32. (a) Find an equation of the tangent line to the curve
y − 3x 1 6 cos x at the point s!y3, ! 1 3d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on the same screen.
;
33. (a) If f sxd − sec x 2 x, find f 9sxd.
(b) Check to see that your answer to part (a) is reasonable
by graphing both f and f 9 for x , !y2.
;
34. (a) If f sxd − e cos x, find f 9sxd and f 99sxd.
(b) Check to see that your answers to part (a) are reasonable by graphing f , f 9, and f 99.
x
; 42. An elastic band is hung on a hook and a mass is hung on the
lower end of the band. When the mass is pulled downward
and then released, it vibrates vertically. The equation of
motion is s − 2 cos t 1 3 sin t, t > 0, where s is measured
in centimeters and t in seconds. (Take the positive direction
to be downward.)
(a) Find the velocity and acceleration at time t.
(b) Graph the velocity and acceleration functions.
(c) When does the mass pass through the equilibrium
position for the first time?
(d) How far from its equilibrium position does the mass
travel?
(e) When is the speed the greatest?
| |
43. A ladder 10 ft long rests against a vertical wall. Let " be the
angle between the top of the ladder and the wall and let x be
the distance from the bottom of the ladder to the wall. If the
bottom of the ladder slides away from the wall, how fast
does x change with respect to " when " − !y3?
sin "
, find t9s"d and t99s"d.
"
44. An object with weight W is dragged along a horizontal
plane by a force acting along a rope attached to the object.
If the rope makes an angle " with the plane, then the magnitude of the force is
x
35. If ts"d −
x
36. If f std − sec t, find f 0s!y4d.
F−
37. (a) Use the Quotient Rule to differentiate the function
f sxd −
tan x 2 1
sec x
(b) Simplify the expression for f sxd by writing it in terms
of sin x and cos x, and then find f 9sxd.
(c) Show that your answers to parts (a) and (b) are equivalent.
38. Suppose f s!y3d − 4 and f 9s!y3d − 22, and let
tsxd − f sxd sin x and hsxd − scos xdyf sxd. Find
(a) t9s!y3d
(b) h9s!y3d
39–40 For what values of x does the graph of f have a horizontal tangent?
39. f sxd − x 1 2 sin x
40. f sxd − e x cos x
;
#W
# sin " 1 cos "
where # is a constant called the coefficient of friction.
(a) Find the rate of change of F with respect to ".
(b) When is this rate of change equal to 0 ?
(c) If W − 50 lb and # − 0.6, draw the graph of F as a
function of " and use it to locate the value of " for
which dFyd" − 0. Is the value consistent with your
answer to part (b)?
45–60 Find the limit.
sin 5x
3x
46. lim
sin 3t
t l 0 sin t
48. lim
45. lim
xl 0
47. lim
sin x
xl 0 sin !x
sin2 3x
xl0
x
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.4
49. lim
sin x 2 sin x cos x
x2
50. lim
51. lim
tan 2x
x
52. lim
sin 3x
x l 0 5x 3 2 4x
54. lim
x l0
xl0
sin "
sin "
A(¨ )
xl 0
P
sinsx 2 d
xl0
x
cos " 2 1
"l0
2" 2
58. lim
1 2 tan x
60. lim
sinsx 2 1d
10 cm
10 cm
¨
R
61–62 Find the given derivative by finding the first few
derivatives and observing the pattern that occurs.
61.
d 99
ssin xd
dx 99
62.
d 35
sx sin xd
dx 35
67. The figure shows a circular arc of length s and a chord of
length d, both subtended by a central angle ". Find
lim
d
1
.
x
1
(b) Evaluate lim x sin .
xl0
x
(c) Illustrate parts (a) and (b) by graphing y − x sins1yxd.
xl`
sin x
(a) tan x −
cos x
(c) sin x 1 cos x −
1
(b) sec x −
cos x
1 1 cot x
csc x
s
¨
64. (a) Evaluate lim x sin
65. Differentiate each trigonometric identity to obtain a new
(or familiar) identity.
s
"l 01 d
63. Find constants A and B such that the function
y − A sin x 1 B cos x satisfies the differential equation
y99 1 y9 2 2y − sin x.
;
Q
B(¨ )
xl1 x2 1 x 2 2
x l !y4 sin x 2 cos x
As"d
lim
"l 01 Bs"d
56. lim csc x sinssin xd
57. lim
199
66. A semicircle with diameter PQ sits on an isosceles triangle
PQR to form a region shaped like a two-dimensional icecream cone, as shown in the figure. If As"d is the area of the
semicircle and Bs"d is the area of the triangle, find
sin 3x sin 5x
xl0
x2
"l 0 " 1 tan "
59. lim
1 2 sec x
2x
"l0 tan 7"
53. lim
55. lim
xl0
The Chain Rule
; 68. Let f sxd −
x
s1 2 cos 2x
.
(a) Graph f . What type of discontinuity does it appear to
have at 0?
(b) Calculate the left and right limits of f at 0. Do these
values confirm your answer to part (a)?
3.4 The Chain Rule
Suppose you are asked to differentiate the function
Fsxd − sx 2 1 1
See Section 1.3 for a review of
composite functions.
The differentiation formulas you learned in the previous sections of this chapter do not
enable you to calculate F9sxd.
Observe that F is a composite function. In fact, if we let y − f sud − su and let
u − tsxd − x 2 1 1, then we can write y − Fsxd − f stsxdd, that is, F − f 8 t. We know
how to differentiate both f and t, so it would be useful to have a rule that tells us how to
find the derivative of F − f 8 t in terms of the derivatives of f and t.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
200
CHAPTER 3
Differentiation Rules
■ The Chain Rule
It turns out that the derivative of the composite function f 8 t is the product of the derivatives of f and t. This fact is one of the most important of the differentiation rules and is
called the Chain Rule. It seems plausible if we interpret derivatives as rates of change.
Regard duydx as the rate of change of u with respect to x, dyydu as the rate of change of
y with respect to u, and dyydx as the rate of change of y with respect to x. If u changes
twice as fast as x and y changes three times as fast as u, then it seems reasonable that
y changes six times as fast as x, and so we expect that dyydx is the product of dyydu
and duydx .
The Chain Rule If t is differentiable at x and f is differentiable at tsxd, then the
composite function F − f 8 t defined by Fsxd − f s tsxdd is differentiable at x and
F9 is given by the product
F9sxd − f 9stsxdd ? t9sxd
1
In Leibniz notation, if y − f sud and u − tsxd are both differentiable functions, then
dy
dy du
−
dx
du dx
2
Formula 2 is easy to remember because if we think of dyydu and duydx as quotients,
then we could cancel du ; however, du has not been defined and duydx should not be
considered as an actual quotient.
James Gregory
The first person to formulate the
Chain Rule was the Scottish mathematician James Gregory (1638 –1675),
who also designed the first practical
reflecting telescope. Gregory discovered the basic ideas of calculus at
about the same time as Newton. He
became the first Professor of Mathematics at the University of St. Andrews
and later held the same position at
the University of Edinburgh. But one
year after accepting that position, he
died at the age of 36.
COMMENTS ON THE PROOF OF THE CHAIN RULE Let Du be the change in u
corresponding to a change of Dx in x, that is,
Du − tsx 1 Dxd 2 tsxd
Then the corresponding change in y is
Dy − f su 1 Dud 2 f sud
It is tempting to write
dy
Dy
− lim
Dxl 0 Dx
dx
3
Dy Du
!
Dx l 0 Du
Dx
− lim
Dy
Du
! lim
Dx l 0 Du
Dx l 0 Dx
− lim
Dy
Du
! lim
Du l 0 Du
Dx l 0 Dx
− lim
−
(Note that Du l 0 as Dx l 0
because t is continuous.)
dy du
du dx
The only flaw in this reasoning is that in (3) it might happen that Du − 0 (even when
Dx ± 0) and, of course, we can’t divide by 0. Nonetheless, this reasoning does at least
suggest that the Chain Rule is true. A full proof of the Chain Rule is given at the end of
this section.
n
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.4
The Chain Rule
201
EXAMPLE 1 Find F9sxd if Fsxd − sx 2 1 1.
SOLUTION 1 (using Formula 1): At the beginning of this section we expressed F as
Fsxd − s f 8 tdsxd − f stsxdd where f sud − su and tsxd − x 2 1 1. Since
f 9sud − 12 u21y2 −
1
t9sxd − 2x
and
2 su
F9sxd − f 9s tsxdd ! t9sxd
we have
−
1
2 sx 2 1 1
! 2x −
x
sx 2 1 1
SOLUTION 2 (using Formula 2): If we let u − x 2 1 1 and y − su , then
dy du
1
1
x
−
s2xd −
s2xd −
du dx
2 su
2 sx 2 1 1
sx 2 1 1
F9sxd −
n
When using Formula 2 we should bear in mind that dyydx refers to the derivative of
y when y is considered as a function of x (the derivative of y with respect to x), whereas
dyydu refers to the derivative of y when considered as a function of u (the derivative of
y with respect to u). For instance, in Example 1, y can be considered as a function of
x ( y − s x 2 1 1 ) and also as a function of u ( y − su ). Note that
dy
x
− F9sxd −
2
dx
sx 1 1
dy
1
− f 9sud −
du
2 su
whereas
NOTE In using the Chain Rule we work from the outside to the inside. Formula 1 says
that we differentiate the outer function f [at the inner function tsxd] and then we multiply
by the derivative of the inner function.
d
dx
f
s tsxdd
outer
function
evaluated
at inner
function
f9
s tsxdd
derivative
of outer
function
evaluated
at inner
function
−
t9sxd
!
derivative
of inner
function
EXAMPLE 2 Differentiate (a) y − sinsx 2 d and (b) y − sin2x.
SOLUTION
(a) If y − sinsx 2 d, then the outer function is the sine function and the inner function is
the squaring function, so the Chain Rule gives
dy
d
−
dx
dx
sin
sx 2 d
outer
function
evaluated
at inner
function
cos
sx 2 d
derivative
of outer
function
evaluated
at inner
function
−
!
2x
derivative
of inner
function
− 2x cossx 2 d
(b) Note that sin2x − ssin xd2. Here the outer function is the squaring function and the
inner function is the sine function. So
dy
d
−
ssin xd2
dx
dx
inner
function
See Reference Page 2 or Appendix D.
−
2
!
ssin xd
!
cos x
derivative
evaluatedevaluated
derivative derivative
derivative
derivative
derivative
evaluated
evaluated
derivative
derivative
of outerofofof
at inner atatinner
outer
outer
outer
atinner
inner of inner ofofof
inner
inner
inner
functionfunction
function function
function
functionfunction function
function
function
function
function
The answer can be left as 2 sin x cos x or written as sin 2x (by a trigonometric identity
known as the double-angle formula).
n
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202
CHAPTER 3
Differentiation Rules
In Example 2(a) we combined the Chain Rule with the rule for differentiating the sine
function. In general, if y − sin u, where u is a differentiable function of x, then, by the
Chain Rule,
dy
dy du
du
−
− cos u
dx
du dx
dx
d
du
ssin ud − cos u
dx
dx
Thus
In a similar fashion, all of the formulas for differentiating trigonometric functions can
be combined with the Chain Rule.
Let’s make explicit the special case of the Chain Rule where the outer function f is a
power function. If y − ftsxdg n, then we can write y − f sud − u n where u − tsxd. By
using the Chain Rule and then the Power Rule, we get
dy
dy du
du
−
− nu n21
− nftsxdg n21 t9sxd
dx
du dx
dx
4 The Power Rule Combined with the Chain Rule If n is any real number
and u − tsxd is differentiable, then
d
du
su n d − nu n21
dx
dx
d
ftsxdg n − n f tsxdg n21 ! t9sxd
dx
Alternatively,
Notice that the derivative we found in Example 1 could be calculated by taking
n − 12 in Rule 4.
EXAMPLE 3 Differentiate y − sx 3 2 1d100.
SOLUTION Taking u − tsxd − x 3 2 1 and n − 100 in (4), we have
dy
d
d
−
sx 3 2 1d100 − 100sx 3 2 1d99
sx 3 2 1d
dx
dx
dx
− 100sx 3 2 1d99 ! 3x 2 − 300x 2sx 3 2 1d99
EXAMPLE 4 Find f 9sxd if f sxd − 3
1
sx 2 1 x 1 1
SOLUTION First rewrite f :
Thus
n
.
f sxd − sx 2 1 x 1 1d21y3
f 9sxd − 213 sx 2 1 x 1 1d24y3
d
sx 2 1 x 1 1d
dx
− 213 sx 2 1 x 1 1d24y3s2x 1 1d
n
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SECTION 3.4
The Chain Rule
203
EXAMPLE 5 Find the derivative of the function
tstd −
S D
t22
2t 1 1
9
SOLUTION Combining the Power Rule, Chain Rule, and Quotient Rule, we get
S D S D
S D
t9std − 9
t22
2t 1 1
8
d
dt
t22
2t 1 1
8
−9
s2t 1 1d ! 1 2 2st 2 2d
45st 2 2d8
−
2
s2t 1 1d
s2t 1 1d10
t22
2t 1 1
n
EXAMPLE 6 Differentiate y − s2x 1 1d5sx 3 2 x 1 1d4.
SOLUTION In this example we must use the Product Rule before using the Chain Rule:
The graphs of the functions y and y9
in Example 6 are shown in Figure 1.
Notice that y9 is large when y
increases rapidly and y9 − 0 when y
has a horizontal tangent. So our
answer appears to be reasonable.
dy
d
d
− s2x 1 1d5
sx 3 2 x 1 1d4 1 sx 3 2 x 1 1d4
s2x 1 1d5
dx
dx
dx
− s2x 1 1d5 ! 4sx 3 2 x 1 1d3
d
sx 3 2 x 1 1d
dx
1 sx 3 2 x 1 1d4 ! 5s2x 1 1d4
10
yª
d
s2x 1 1d
dx
− 4s2x 1 1d5sx 3 2 x 1 1d3s3x 2 2 1d 1 5sx 3 2 x 1 1d4s2x 1 1d4 ! 2
_2
1
y
_10
FIGURE 1
Noticing that each term has the common factor 2s2x 1 1d4sx 3 2 x 1 1d3, we could
factor it out and write the answer as
dy
− 2s2x 1 1d4sx 3 2 x 1 1d3s17x 3 1 6x 2 2 9x 1 3d
dx
n
EXAMPLE 7 Differentiate y − e sin x.
SOLUTION Here the inner function is tsxd − sin x and the outer function is the
exponential function f sxd − e x. So, by the Chain Rule,
More generally, the Chain Rule gives
d u
du
se d − e u
dx
dx
dy
d
d
−
se sin x d − e sin x
ssin xd − e sin x cos x
dx
dx
dx
n
The reason for the name “Chain Rule” becomes clear when we make a longer chain
by adding another link. Suppose that y − f sud, u − tsxd, and x − hstd where f , t, and h
are differentiable functions. Then, to compute the derivative of y with respect to t, we use
the Chain Rule twice:
dy
dy dx
dy du dx
−
−
dt
dx dt
du dx dt
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204
CHAPTER 3
Differentiation Rules
EXAMPLE 8 If f sxd − sinscosstan xdd, then
f 9sxd − cosscosstan xdd
d
cosstan xd
dx
d
stan xd
dx
− 2cosscosstan xdd sinstan xd sec2x
− cosscosstan xdd f2sinstan xdg
Notice that we used the Chain Rule twice.
n
EXAMPLE 9 Differentiate y − e sec 3".
SOLUTION The outer function is the exponential function, the middle function is the
secant function, and the inner function is the tripling function. So we have
dy
d
− e sec 3"
ssec 3"d
d"
d"
d
s3"d
d"
− 3e sec 3" sec 3" tan 3"
− e sec 3" sec 3" tan 3"
n
■ Derivatives of General Exponential Functions
We can use the Chain Rule to differentiate an exponential function with any base b . 0.
Recall from Equation 1.5.10 that we can write
b x − e sln bdx
and then the Chain Rule gives
d
d
d
sb x d −
se sln bdx d − e sln bdx
[sln bdx]
dx
dx
dx
− e sln bdx sln bd − b x ln b
because ln b is a constant. So we have the formula
Don’t confuse Formula 5 (where x is
the exponent) with the Power Rule
(where x is the base):
d
sb x d − b x ln b
dx
5
d
sx n d − nx n21
dx
EXAMPLE 10 Find the derivative of each of the functions.
(a) tsxd − 2 x
(b) hsxd − 5 x
2
SOLUTION
(a) We use Formula 5 with b − 2:
t9sxd −
d
s2 x d − 2 x ln 2
dx
This is consistent with the estimate
d
s2 x d < s0.693d2 x
dx
we gave in Section 3.1 because ln 2 < 0.693147.
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SECTION 3.4
The Chain Rule
205
(b) The outer function is an exponential function and the inner function is the squaring
function, so we use Formula 5 and the Chain Rule to get
h9sxd −
d
(5 x 2) − 5 x 2 ln 5 ? d sx 2d − 2x ? 5 x 2 ln 5
dx
dx
n
■ How to Prove the Chain Rule
Recall that if y − f sxd and x changes from a to a 1 Dx, we define the increment of y as
Dy − f sa 1 Dxd 2 f sad
According to the definition of a derivative, we have
lim
Dy
Dx l 0 Dx
− f 9sad
So if we denote by « the difference between DyyDx and f 9sad, we obtain
lim « − lim
Dx l 0
But
«−
Dx l 0
S
D
Dy
2 f 9sad − f 9sad 2 f 9sad − 0
Dx
Dy
2 f 9sad
Dx
?
Dy − f 9sad Dx 1 « Dx
If we define « to be 0 when Dx − 0, then « becomes a continuous function of Dx. Thus,
for a differentiable function f, we can write
6
Dy − f 9sad Dx 1 « Dx
where
« l 0 as Dx l 0
and « is a continuous function of Dx. This property of differentiable functions is what
enables us to prove the Chain Rule.
PROOF OF THE CHAIN RULE Suppose u − tsxd is differentiable at a and y − f sud is
differentiable at b − tsad. If Dx is an increment in x and Du and Dy are the corresponding increments in u and y, then we can use Equation 6 to write
7
Du − t9sad Dx 1 «1 Dx − ft9sad 1 «1 g Dx
where «1 l 0 as Dx l 0. Similarly
8
Dy − f 9sbd Du 1 «2 Du − f f 9sbd 1 «2 g Du
where «2 l 0 as Du l 0. If we now substitute the expression for Du from Equation 7
into Equation 8, we get
Dy − f f 9sbd 1 «2 gft9sad 1 «1 g Dx
Dy
− f f 9sbd 1 «2 gf t9sad 1 «1 g
Dx
so
As Dx l 0, Equation 7 shows that Du l 0. Taking the limit as Dx l 0 , we get
dy
Dy
− lim
− lim f f 9sbd 1 «2 gft9sad 1 «1 g
Dx
l
0
Dx l 0
dx
Dx
− f 9sbd t9sad − f 9stsadd t9sad
This proves the Chain Rule.
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n
206
CHAPTER 3
Differentiation Rules
3.4 Exercises
1–6 Write the composite function in the form f s tsxdd.
[Identify the inner function u − tsxd and the outer function
y − f sud.] Then find the derivative dyydx.
2
2
47. f sxd − esin sx d
48. y − 23
4x
2
49. y − s3cossx d 2 1d4
1. y − s5 2 x 4d3
2. y − sx 3 1 2
50. y − sins" 1 tans" 1 cos "dd
3. y − sinscos xd
4. y − tansx 2 d
51. y − cos ssinstan !xd
5. y − esx
3
6. y − s
ex 1 1
52. y − sin3scossx 2 dd
53–56 Find y9 and y 99.
7–52 Find the derivative of the function.
7. f sxd − s2x 3 2 5x 2 1 4d5
8. f sxd − sx 5 1 3x 2 2 xd50
9. f sxd − s5x 1 1
10. f sxd −
1
3
x2 2 1
s
S D
1
11. tstd −
s2t 1 1d2
12. Fstd −
13. f s"d − coss" d
14. ts"d − cos "
15. tsxd − e x 2x
16. y − 5sx
17. y − x 2e 23x
18. f std − t sin !t
19. f std − e at sin bt
20. Asrd − sr ? e r 11
2
1
2t 1 1
23. y −
Î
25. y − e tan "
27. tsud −
S
u3 2 1
u3 1 1
D
28. sstd −
1 1 sin t
1 1 cos t
29. rstd − 10 2st
30. f szd − e zysz21d
sr 2 2 1d 3
31. Hsrd −
s2r 1 1d 5
32. Js"d − tan sn"d
33. Fstd − e t sin 2t
34. Fstd −
35. Gsxd − 4 Cyx
36. Us yd −
37. f sxd − sin x coss1 2 x 2 d
38. tsxd − e2x cossx 2 d
39. Fstd − tan s1 1 t 2
40. Gszd − s1 1 cos2zd3
41. y − sin2sx 2 1 1d
42. y − e sin 2x 1 sinse 2x d
ex
43. tsxd − sin
1 1 ex
44. f std − e st 2 1
45. f std − tanssecscos tdd
46. y − sx 1 sx 1 s x
S D
2
t2
st 1 1
3
S D
y4 1 1
y2 1 1
1yt
58. y − s1 1 x 3 ,
60. y − xe
2x 2
s2, 3d
, s0, 0d
| |
3
Î
x
62. (a) The curve y − x ys2 2 x 2 is called a bullet-nose
curve. Find an equation of the tangent line to this curve at
the point s1, 1d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on the same screen.
S D
8
3
61. (a) Find an equation of the tangent line to the curve
y − 2ys1 1 e2x d at the point s0, 1d.
(b)
Illustrate
part (a) by graphing the curve and the tangent
;
line on the same screen.
5
1
24. y − x 1
x
26. f std − 2 t
56. y − e e
59. y − sinssin xd, s!, 0d
21. Fsxd − s4x 1 5d 3sx 2 2 2x 1 5d4
x
x11
55. y − scos x
57. y − 2 x, s0, 1d
2
22. Gszd − s1 2 4zd2sz 2 1 1
54. y − (1 1 sx )
57–60 Find an equation of the tangent line to the curve at the
given point.
4
2
2
53. y − cosssin 3"d
5
2
63. (a) If f sxd − x s2 2 x 2 , find f 9sxd.
(b) Check to see that your answer to part (a) is reasonable by
;
comparing the graphs of f and f 9.
; 64. The function f sxd − sinsx 1 sin 2xd, 0 < x < !, arises in
applications to frequency modulation (FM) synthesis.
(a) Use a graph of f produced by a calculator or computer to
make a rough sketch of the graph of f 9.
(b) Calculate f 9sxd and use this expression, with a calculator
or computer, to graph f 9. Compare with your sketch in
part (a).
65. Find all points on the graph of the function
f sxd − 2 sin x 1 sin2x at which the tangent line is horizontal.
66. At what point on the curve y − s1 1 2x is the tangent line
perpendicular to the line 6x 1 2y − 1?
67. If Fsxd − f stsxdd, where f s22d − 8, f 9s22d − 4, f 9s5d − 3,
ts5d − 22, and t9s5d − 6, find F9s5d.
68. If hsxd − s4 1 3f sxd , where f s1d − 7 and f 9s1d − 4,
find h9s1d.
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SECTION 3.4
69. A table of values for f , t, f 9, and t9 is given.
x
f sxd
tsxd
f 9sxd
t9sxd
1
2
3
3
1
7
2
8
2
4
5
7
6
7
9
(a) If hsxd − f stsxdd, find h9s1d.
(b) If Hsxd − ts f sxdd, find H9s1d.
70. Let f and t be the functions in Exercise 69.
(a) If Fsxd − f s f sxdd, find F9s2d.
(b) If Gsxd − tstsxdd, find G9s3d.
71. If f and t are the functions whose graphs are shown, let
usxd − f s tsxdd, vsxd − ts f sxdd, and w sxd − ts tsxdd. Find
each derivative, if it exists. If it does not exist, explain why.
(a) u9s1d
(b) v9s1d
(c) w9s1d
y
The Chain Rule
207
74. Suppose f is differentiable on R and $ is a real number.
Let Fsxd − f sx $ d and Gsxd − f f sxdg $. Find expressions
for (a) F9sxd and (b) G9sxd.
75. Suppose f is differentiable on R. Let Fsxd − f se x d and
Gsxd − e f sxd. Find expressions for (a) F9sxd and (b) G9sxd.
76. Let tsxd − e cx 1 f sxd and hsxd − e kx f sxd, where f s0d − 3,
f 9s0d − 5, and f 99s0d − 22.
(a) Find t9s0d and t99s0d in terms of c.
(b) In terms of k, find an equation of the tangent line to the
graph of h at the point where x − 0.
77. Let rsxd − f s tshsxddd, where hs1d − 2, ts2d − 3, h9s1d − 4,
t9s2d − 5, and f 9s3d − 6. Find r9s1d.
78. If t is a twice differentiable function and f sxd − x tsx 2 d, find
f 99 in terms of t, t9, and t99.
79. If Fsxd − f s3f s4 f sxddd, where f s0d − 0 and f 9s0d − 2,
find F9s0d.
80. If Fsxd − f sx f sx f sxddd, where f s1d − 2, f s2d − 3,
f 9s1d − 4, f 9s2d − 5, and f 9s3d − 6, find F9s1d.
81. Show that the function y − e 2x sA cos 3x 1 B sin 3xd satisfies
the differential equation y99 2 4y9 1 13y − 0.
f
82. For what values of r does the function y − e rx satisfy the
differential equation y99 2 4y9 1 y − 0 ?
g
1
83. Find the 50th derivative of y − cos 2x.
0
1
x
72. If f is the function whose graph is shown, let hsxd − f s f sxdd
and tsxd − f sx 2 d. Use the graph of f to estimate the value
of each derivative.
(a) h9s2d
(b) t9s2d
y
1
1
85. The displacement of a particle on a vibrating string is given
by the equation
sstd − 10 1 14 sins10!td
where s is measured in centimeters and t in seconds. Find the
velocity of the particle after t seconds.
86. If the equation of motion of a particle is given by
s − A coss%t 1 &d, the particle is said to undergo simple
harmonic motion.
(a) Find the velocity of the particle at time t.
(b) When is the velocity 0 ?
y=ƒ
0
84. Find the 1000th derivative of f sxd − xe2x.
x
73. If tsxd − sf sxd , where the graph of f is shown,
evaluate t9s3d.
y
87. A Cepheid variable star is a star whose brightness alternately
increases and decreases. The most easily visible such star is
Delta Cephei, for which the interval between times of maximum brightness is 5.4 days. The average brightness of this
star is 4.0 and its brightness changes by 60.35. In view of
these data, the brightness of Delta Cephei at time t, where t is
measured in days, has been modeled by the function
S D
Bstd − 4.0 1 0.35 sin
f
1
0
1
x
2!t
5.4
(a) Find the rate of change of the brightness after t days.
(b) Find, correct to two decimal places, the rate of increase
after one day.
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208
CHAPTER 3
Differentiation Rules
88. In Example 1.3.4 we arrived at a model for the length of daylight (in hours) in Philadelphia on the t th day of the year:
F
Lstd − 12 1 2.8 sin
2!
st 2 80d
365
G
Use this model to compare how the number of hours of
daylight is increasing in Philadelphia on March 21 st − 80d
and May 21 st − 141d.
; 89. The motion of a spring that is subject to a frictional force or
a damping force (such as a shock absorber in a car) is often
modeled by the product of an exponential function and a
sine or cosine function. Suppose the equation of motion of a
point on such a spring is
sstd − 2e21.5t sin 2!t
where s is measured in centimeters and t in seconds. Find
the velocity after t seconds and graph both the position and
velocity functions for 0 < t < 2.
90. Under certain circumstances a rumor spreads according to
the equation
pstd −
;
1
1 1 ae 2k t
where pstd is the proportion of the population that has heard
the rumor at time t and a and k are positive constants. [In
Section 9.4 we will see that this is a reasonable equation
for pstd.]
(a) Find lim t l ` pstd and interpret your answer.
(b) Find the rate of spread of the rumor.
(c) Graph p for the case a − 10, k − 0.5 with t measured
in hours. Use the graph to estimate how long it will take
for 80% of the population to have heard the rumor.
93. A particle moves along a straight line with displacement
sstd, velocity vstd, and acceleration astd. Show that
astd − vstd
dv
ds
Explain the difference between the meanings of the derivatives dvydt and dvyds.
94. The table gives the US population from 1790 to 1860.
Year
Population
Year
Population
1790
1800
1810
1820
3,929,000
5,308,000
7,240,000
9,639,000
1830
1840
1850
1860
12,861,000
17,063,000
23,192,000
31,443,000
(a) Fit an exponential function to the data. Graph the data
points and the exponential model. How good is the fit?
(b) Estimate the rates of population growth in 1800 and
1850 by averaging slopes of secant lines.
(c) Use the exponential model in part (a) to estimate the
rates of growth in 1800 and 1850. Compare these
estimates with the ones in part (b).
(d) Use the exponential model to predict the population in 1870. Compare with the actual population of
38,558,000. Can you explain the discrepancy?
95. Use the Chain Rule to prove the following.
(a) The derivative of an even function is an odd function.
(b) The derivative of an odd function is an even function.
96. Use the Chain Rule and the Product Rule to give an alternative proof of the Quotient Rule.
[Hint: Write f sxdytsxd − f sxdf tsxdg 21.]
91. The average blood alcohol concentration (BAC) of eight
male subjects was measured after consumption of 15 mL of
ethanol (corresponding to one alcoholic drink). The resulting data were modeled by the concentration function
97. Use the Chain Rule to show that if " is measured in degrees,
then
d
!
ssin "d −
cos "
d"
180
Cstd − 0.00225te 20.0467t
(This gives one reason for the convention that radian measure is always used when dealing with trigonometric functions in calculus: the differentiation formulas would not be
as simple if we used degree measure.)
where t is measured in minutes after consumption and C is
measured in gydL.
(a) How rapidly was the BAC increasing after 10 minutes?
(b) How rapidly was it decreasing half an hour later?
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of Ethanol after
Oral Administration in the Fasting State,” Journal of Pharmacokinetics and
Biopharmaceutics 5 (1977): 207–24.
92. Air is being pumped into a spherical weather balloon. At any
time t, the volume of the balloon is Vstd and its radius is rstd.
(a) What do the derivatives dVydr and dVydt represent?
(b) Express dVydt in terms of drydt.
| |
98. (a) Write x − sx 2 and use the Chain Rule to show that
d
x −
dx
| |
|
|
x
x
| |
(b) If f sxd − sin x , find f 9sxd and sketch the graphs of f
and f 9. Where is f not differentiable?
(c) If tsxd − sin x , find t9sxd and sketch the graphs of t
and t9. Where is t not differentiable?
| |
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.5
99. Let c be the x-intercept of the tangent line to the curve y − b x
sb . 0, b ± 1d at the point sa, b a d. Show that the distance
between the points sa, 0d and sc, 0d is the same for all values
of a.
y=b x
100. On every exponential curve y − b x sb . 0, b ± 1d, there is
exactly one point sx 0, y 0d at which the tangent line to the
curve passes through the origin. Show that in every case,
y0 − e. [Hint: You may wish to use Formula 1.5.10.]
F9sxd − f 9s tshsxdd ? t9shsxdd ? h9sxd
102. If F − f + t, where f and t are twice differentiable functions, use the Chain Rule and the Product Rule to show that
the second derivative of F is given by
(a, b a)
c
209
101. If F − f + t + h , where f , t, and h are differentiable functions, use the Chain Rule to show that
y
0
Implicit Differentiation
F 0sxd − f 0s tsxdd ? [ t9sxd] 2 1 f 9s tsxdd ? t 0sxd
x
a
APPLIED PROJECT WHERE SHOULD A PILOT START DESCENT?
y
An approach path for an aircraft landing is shown in the figure and satisfies the following
conditions:
(i) The cruising altitude is h when descent starts at a horizontal distance , from touchdown at the origin.
y=P(x)
0
!
(ii) The pilot must maintain a constant horizontal speed v throughout descent.
h
(iii) The absolute value of the vertical acceleration should not exceed a constant k (which
is much less than the acceleration due to gravity).
x
1. Find a cubic polynomial Psxd − ax 3 1 bx 2 1 cx 1 d that satisfies condition (i) by
imposing suitable conditions on Psxd and P9sxd at the start of descent and at touchdown.
2. Use conditions (ii) and (iii) to show that
6h v 2
<k
,2
3. Suppose that an airline decides not to allow vertical acceleration of a plane to exceed
k − 860 miyh2. If the cruising altitude of a plane is 35,000 ft and the speed is 300 miyh,
how far away from the airport should the pilot start descent?
; 4. Graph the approach path if the conditions stated in Problem 3 are satisfied.
3.5 Implicit Differentiation
■ Implicitly Defined Functions
The functions that we have met so far can be described by expressing one variable explicitly in terms of another variable —for example,
y − sx 3 1 1
or
y − x sin x
or, in general, y − f sxd. Some functions, however, are defined implicitly by a relation
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210
CHAPTER 3
Differentiation Rules
between x and y such as
1
x 2 1 y 2 − 25
2
x 3 1 y 3 − 6xy
or
In some cases it is possible to solve such an equation for y as an explicit function (or several functions) of x. For instance, if we solve Equation 1 for y, we get y − 6s25 2 x 2 ,
so two of the functions determined by the implicit Equation l are f sxd − s25 2 x 2 and
tsxd − 2s25 2 x 2 . The graphs of f and t are the upper and lower semicircles of the
circle x 2 1 y 2 − 25. (See Figure 1.)
y
0
FIGURE 1
y
x
(a) ≈+¥=25
y
0
0
x
25-≈
(b) ƒ=œ„„„„„„
x
25-≈
(c) ©=_ œ„„„„„„
It’s not easy to solve Equation 2 for y explicitly as a function of x by hand. (Even if
we use technology, the resulting expressions are very complicated.) Nonetheless, (2) is
the equation of a curve called the folium of Descartes shown in Figure 2 and it implicitly
defines y as several functions of x. The graphs of three such functions are shown in Figure 3. When we say that f is a function defined implicitly by Equation 2, we mean that
the equation
x 3 1 f f sxdg 3 − 6x f sxd
is true for all values of x in the domain of f .
y
0
˛+Á=6xy
x
FIGURE 2 The folium of Descartes
y
0
y
x
0
y
x
0
x
FIGURE 3 Graphs of three functions defined implicitly by the folium of Descartes
■ Implicit Differentiation
Fortunately, we don’t need to solve an equation for y in terms of x in order to find the
derivative of y. Instead we can use the method of implicit differentiation. This consists
of differentiating both sides of the equation with respect to x and then solving the resulting equation for dyydx. In the examples and exercises of this section it is always assumed
that the given equation determines y implicitly as a differentiable function of x so that the
method of implicit differentiation can be applied.
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SECTION 3.5
Implicit Differentiation
211
EXAMPLE 1
dy
. Then find an equation of the tangent to the circle
dx
2
2
x 1 y − 25 at the point s3, 4d.
If x 2 1 y 2 − 25, find
SOLUTION 1
Differentiate both sides of the equation x 2 1 y 2 − 25:
d
d
sx 2 1 y 2 d −
s25d
dx
dx
d
d
sx 2 d 1
sy 2 d − 0
dx
dx
Remembering that y is a function of x and using the Chain Rule, we have
d
d
dy
dy
sy 2 d −
sy 2 d
− 2y
dx
dy
dx
dx
dy
Thus
2x 1 2y
−0
dx
Now we solve this equation for dyydx:
dy
x
−2
dx
y
At the point s3, 4d we have x − 3 and y − 4, so
dy
3
−2
dx
4
An equation of the tangent to the circle at s3, 4d is therefore
y 2 4 − 234 sx 2 3d
or
3x 1 4y − 25
SOLUTION 2
Solving the equation x 2 1 y 2 − 25 for y, we get y − 6s25 2 x 2 . The point
s3, 4d lies on the upper semicircle y − s25 2 x 2 and so we consider the function
f sxd − s25 2 x 2 . Differentiating f using the Chain Rule, we have
f 9sxd − 12 s25 2 x 2 d21y2
d
s25 2 x 2 d
dx
− 12 s25 2 x 2 d21y2s22xd − 2
x
s25 2 x 2
At the point s3, 4d we have
Example 1 illustrates that even when
it is possible to solve an equation
explicitly for y in terms of x, it may be
easier to use implicit differentiation.
f 9s3d − 2
3
s25 2 32
−2
3
4
and, as in Solution 1, an equation of the tangent is 3x 1 4y − 25.
n
NOTE 1 The expression dyydx − 2xyy in Solution 1 gives the derivative in terms of
both x and y. It is correct no matter which function y is determined by the given equation.
For instance, for y − f sxd − s25 2 x 2 we have
dy
x
x
−2 −2
dx
y
s25 2 x 2
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212
CHAPTER 3
Differentiation Rules
whereas for y − tsxd − 2s25 2 x 2 we have
dy
x
x
x
−2 −2
−
2
dx
y
2s25 2 x
s25 2 x 2
EXAMPLE 2
(a) Find y9 if x 3 1 y 3 − 6xy.
(b) Find the tangent to the folium of Descartes x 3 1 y 3 − 6xy at the point s3, 3d.
(c) At what point in the first quadrant is the tangent line horizontal?
We can use either of the notations
dyydx or y9 for the derivative of y
with respect to x.
y
SOLUTION
(a) Differentiating both sides of x 3 1 y 3 − 6xy with respect to x, regarding y as a
function of x, and using the Chain Rule on the term y 3 and the Product Rule on the
term 6xy, we get
3x 2 1 3y 2 y9 − 6xy9 1 6y
or
x 2 1 y 2 y9 − 2xy9 1 2y
We now solve for y9:
y 2 y9 2 2xy9 − 2y 2 x 2
s y 2 2 2xdy9 − 2y 2 x 2
(3, 3)
y9 −
0
x
2y 2 x 2
y 2 2 2x
(b) When x − y − 3,
y9 −
FIGURE 4
2 ! 3 2 32
− 21
32 2 2 ! 3
and a glance at Figure 4 confirms that this is a reasonable value for the slope at s3, 3d.
So an equation of the tangent to the folium at s3, 3d is
4
y 2 3 − 21sx 2 3d
or
x1y−6
(c) The tangent line is horizontal if y9 − 0. Using the expression for y9 from part (a),
we see that y9 − 0 when 2y 2 x 2 − 0 (provided that y 2 2 2x ± 0d. Substituting
y − 12 x 2 in the equation of the curve, we get
x 3 1 ( 12 x 2) − 6x ( 12 x 2)
3
4
0
FIGURE 5
which simplifies to x 6 − 16x 3. Since x ± 0 in the first quadrant, we have x 3 − 16. If
x − 16 1y3 − 2 4y3, then y − 12 s2 8y3 d − 2 5y3. Thus the tangent is horizontal at s2 4y3, 2 5y3 d,
which is approximately (2.5198, 3.1748). Looking at Figure 5, we see that our answer
is reasonable.
n
NOTE 2 There is a formula for the three solutions of a cubic equation that is like the
quadratic formula but much more complicated. If we use this formula (or a computer) to
solve the equation x 3 1 y 3 − 6xy for y in terms of x, we get three functions determined
by the equations:
y − f sxd − s221 x 3 1 s14 x 6 2 8x 3 1 s221 x 3 2 s14 x 6 2 8x 3
3
3
and
f
g
y − 12 2f sxd 6 s23 (s221 x 3 1 s14 x 6 2 8x 3 2 s221 x 3 2 s14 x 6 2 8x 3 )
3
3
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SECTION 3.5
213
Implicit Differentiation
(These are the three functions whose graphs are shown in Figure 3.) You can see that the
method of implicit differentiation saves an enormous amount of work in cases such as
this. Moreover, implicit differentiation works just as easily for equations such as
Abel and Galois
The Norwegian mathematician Niels
Abel proved in 1824 that no general
formula in terms of radicals can be
given for the solutions of the equation
psxd − 0, where p is a polynomial of
degree 5 with integer coefficients.
Later the French mathematician
Evariste Galois proved that it is impossible to find a general formula in
terms of radicals for the solutions of
an equation psxd − 0, where p is a
polynomial of degree n > 5 .
y 5 1 3x 2 y 2 1 5x 4 − 12
for which it is impossible to find an expression for y in terms of x.
EXAMPLE 3 Find y9 if sinsx 1 yd − y 2 cos x.
SOLUTION Differentiating implicitly with respect to x and remembering that y is a
function of x, we get
cossx 1 yd ! s1 1 y9d − y 2s2sin xd 1 scos xds2yy9d
(Note that we have used the Chain Rule on the left side and the Product Rule and Chain
Rule on the right side.) If we collect the terms that involve y9, we get
2
cossx 1 yd 1 y 2 sin x − s2y cos xdy9 2 cossx 1 yd ! y9
_2
So
2
y9 −
y 2 sin x 1 cossx 1 yd
2y cos x 2 cossx 1 yd
Figure 6, drawn by a computer, shows part of the curve sinsx 1 yd − y 2 cos x. As a
check on our calculation, notice that y9 − 21 when x − y − 0 and it appears from the
graph that the slope is approximately 21 at the origin.
n
_2
Figures 7, 8, and 9 show three more curves produced by a computer. In Exercises 45–46
you will have an opportunity to create and examine unusual curves of this nature.
FIGURE 6
4
_4
15
4
_15
12
15
_4
_15
FIGURE 7
sx 2 2 1dsx 2 2 4dsx 2 2 9d
− y 2 s y 2 2 4ds y 2 2 9d
FIGURE 8
cossx 2 sin yd − sins y 2 sin xd
_12
12
_12
FIGURE 9
sinsxyd − sin x 1 sin y
■ Second Derivatives of Implicit Functions
The following example shows how to find the second derivative of a function that is
defined implicitly.
EXAMPLE 4 Find y99 if x 4 1 y 4 − 16.
SOLUTION Differentiating the equation implicitly with respect to x, we get
4x 3 1 4y 3 y9 − 0
Solving for y9 gives
3
y9 − 2
x3
y3
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214
CHAPTER 3
Differentiation Rules
To find y99 we differentiate this expression for y9 using the Quotient Rule and remembering that y is a function of x:
S D
d
x3
y 3 sdydxdsx 3 d 2 x 3 sdydxds y 3 d
2 3 −2
dx
y
sy 3 d2
3
2
3
2
y ! 3x 2 x s3y y9d
−2
y6
y99 −
If we now substitute Equation 3 into this expression, we get
S D
3x 2 y 3 2 3x 3 y 2 2
y99 − 2
x3
y3
y6
3sx 2 y 4 1 x 6 d
3x 2sy 4 1 x 4 d
−2
−2
7
y
y7
But the values of x and y must satisfy the original equation x 4 1 y 4 − 16. So the
answer simplifies to
3x 2s16d
x2
y99 − 2
− 248 7
7
y
y
y
Figure 10 shows the graph of the
curve x 4 1 y 4 − 16 of Example 4.
Notice that it’s a stretched and
flattened version of the circle
x 2 1 y 2 − 4. For this reason it’s
sometimes called a fat circle. It starts
out very steep on the left but quickly
becomes very flat. This can be seen
from the expression
y9 − 2
x $+y$ =16
2
0
SD
x3
x
−2
y3
y
n
2 x
3
FIGURE 10
3.5 Exercises
1–4
(a) Find y9 by implicit differentiation.
(b) Solve the equation explicitly for y and differentiate to get y9
in terms of x.
(c) Check that your solutions to parts (a) and (b) are consistent
by substituting the expression for y into your solution for
part (a).
2
3
4
5
9.
x2
− y2 1 1
x1y
10. xe y − x 2 y
11. sin x 1 cos y − 2x 2 3y
12. e x sin y − x 1 y
13. sinsx 1 yd − cos x 1 cos y
14. tansx 2 yd − 2x y 3 1 1
15. y cos x − x 2 1 y 2
16. sinsxyd − cossx 1 yd
1. 5x 2 y − 7
2. 6x 1 y − 2x
17. 2xe 1 ye − 3
18. sin x cos y − x 2 2 5y
3. sx 1 sy − 1
4.
2
1
2 −4
x
y
19. sx 1 y − x 4 1 y 4
20. xy − sx 2 1 y 2
21. e xyy − x 2 y
22. cossx 2 1 y 2 d − xe y
y
x
5–22 Find dyydx by implicit differentiation.
5. x 2 2 4xy 1 y 2 − 4
6. 2x 2 1 xy 2 y 2 − 2
23. If f sxd 1 x 2 f f sxdg 3 − 10 and f s1d − 2, find f 9s1d.
7. x 4 1 x 2 y 2 1 y 3 − 5
8. x 3 2 xy 2 1 y 3 − 1
24. If tsxd 1 x sin tsxd − x 2, find t9s0d.
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SECTION 3.5
25–26 Regard y as the independent variable and x as the
dependent variable and use implicit differentiation to find dxydy.
25. x 4y 2 2 x 3y 1 2xy 3 − 0
26. y sec x − x tan y
27–36 Use implicit differentiation to find an equation of the
tangent line to the curve at the given point.
27. ye sin x − x cos y, s0, 0d
28. tansx 1 yd 1 secsx 2 yd − 2, s!y8, !y8d
29. x 2y3 1 y 2y3 − 4,
30. y s6 2 xd − x ,
2
3
(23 s3, 1) (astroid)
(2, s2 ) (cissoid of Diocles)
31. x 2 2 xy 2 y 2 − 1,
2
s2, 1d
2
32. x 1 2xy 1 4y − 12,
(hyperbola)
s2, 1d
33. x 2 1 y 2 − s2x 2 1 2y 2 2 xd 2,
(ellipse)
(0, 12 )
(cardioid)
y
Implicit Differentiation
215
37. (a) The curve with equation y 2 − 5x 4 2 x 2 is called a
kampyle of Eudoxus. Find an equation of the tangent
line to this curve at the point s1, 2d.
(b) Illustrate part (a) by graphing the curve and the tangent
;
line on a common screen. (Graph the implicitly defined
curve if possible, or you can graph the upper and lower
halves separately.)
38. (a) The curve with equation y 2 − x 3 1 3x 2 is called the
Tschirnhausen cubic. Find an equation of the tangent
line to this curve at the point s1, 22d.
(b) At what points does this curve have horizontal tangents?
(c) Illustrate parts (a) and (b) by graphing the curve and the
;
tangent lines on a common screen.
39–42 Find y99 by implicit differentiation. Simplify where
possible.
39. x 2 1 4y 2 − 4
40. x 2 1 xy 1 y 2 − 3
41. sin y 1 cos x − 1
42. x 3 2 y 3 − 7
43. If xy 1 e y − e, find the value of y99 at the point where x − 0.
x
34. x 2 y 2 − s y 1 1d 2 s4 2 y 2 d,
(conchoid of Nicomedes)
44. If x 2 1 xy 1 y 3 − 1, find the value of y999 at the point
where x − 1.
(2 s3, 1)
ys y 2 2 1ds y 2 2d − xsx 2 1dsx 2 2d
y
0
At how many points does this curve have horizontal
tangents? Estimate the x-coordinates of these points.
(b) Find equations of the tangent lines at the points (0, 1)
and (0, 2).
(c) Find the exact x-coordinates of the points in part (a).
(d) Create even more fanciful curves by modifying the
equation in part (a).
x
35. 2sx 2 1 y 2 d2 − 25sx 2 2 y 2 d, s3, 1d
(lemniscate)
x
0
36. y s y 2 4d − x sx 2 5d,
2
2
s0, 22d
2
; 46. (a) The curve with equation
2y 3 1 y 2 2 y 5 − x 4 2 2x 3 1 x 2
y
2
; 45. Fanciful shapes can be created by using software that can
graph implicitly defined curves.
(a) Graph the curve with equation
(devil’s curve)
has been likened to a bouncing wagon. Graph this curve
and discover why.
(b) At how many points does this curve have horizontal
tangent lines? Find the x-coordinates of these points.
47. Find the points on the lemniscate in Exercise 35 where the
tangent is horizontal.
48. Show by implicit differentiation that the tangent line to
the ellipse
y
x
x2
y2
1
−1
a2
b2
at the point sx 0 , y 0 d has equation
x0 x
y0 y
1 2 −1
a2
b
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216
CHAPTER 3
Differentiation Rules
60. (a) Use implicit differentiation to find y9 if
49. Find an equation of the tangent line to the hyperbola
2
x
y
2 2 −1
a2
b
at the point sx 0 , y 0 d.
50. Show that the sum of the x- and y-intercepts of any tangent
line to the curve sx 1 sy − sc is equal to c.
51. Show, using implicit differentiation, that any tangent line at
a point P to a circle with center O is perpendicular to the
radius OP.
52. The Power Rule can be proved using implicit differentiation
for the case where n is a rational number, n − pyq, and
y − f sxd − x n is assumed beforehand to be a differentiable
function. If y − x pyq, then y q − x p. Use implicit differentiation to show that
p s pyqd21
y9 −
x
q
53–56 Orthogonal Trajectories Two curves are orthogonal if
their tangent lines are perpendicular at each point of intersection.
Show that the given families of curves are orthogonal trajectories
of each other; that is, every curve in one family is orthogonal to
every curve in the other family. Sketch both families of curves on
the same axes.
2
2
2
2
2
53. x 1 y − r ,
54. x 1 y − ax,
55. y − cx 2,
3
56. y − ax ,
;
(b) Plot the curve in part (a). What do you see? Prove that
what you see is correct.
(c) In view of part (b), what can you say about the
expression for y9 that you found in part (a)?
61. The equation x 2 2 xy 1 y 2 − 3 represents a “rotated
ellipse,” that is, an ellipse whose axes are not parallel to the
coordinate axes. Find the points at which this ellipse crosses
the x-axis and show that the tangent lines at these points are
parallel.
62. (a) Where does the normal line to the ellipse
x 2 2 xy 1 y 2 − 3 at the point s21, 1d intersect the
ellipse a second time?
(b) Illustrate part (a) by graphing the ellipse and the
;
normal line.
63. Find all points on the curve x 2 y 2 1 xy − 2 where the slope
of the tangent line is 21.
64. Find equations of both the tangent lines to the ellipse
x 2 1 4y 2 − 36 that pass through the point s12, 3d.
65. Use implicit differentiation to find dyydx for the equation
ax 1 by − 0
x
− y2 1 1
y
x 2 1 y 2 − by
x 2 1 2y 2 − k
2
x 2 1 xy 1 y 2 1 1 − 0
2
and for the equivalent equation
2
x 1 3y − b
57. Show that the ellipse x 2ya 2 1 y 2yb 2 − 1 and the hyperbola
x 2yA2 2 y 2yB 2 − 1 are orthogonal trajectories if A2 , a 2 and
a 2 2 b 2 − A2 1 B 2 (so the ellipse and hyperbola have the
same foci).
58. Find the value of the number a such that the families of
curves y − sx 1 cd21 and y − asx 1 kd1y3 are orthogonal
trajectories.
59. The van der Waals equation for n moles of a gas is
S
D
n 2a
P 1 2 sV 2 nbd − nRT
V
where P is the pressure, V is the volume, and T is the temperature of the gas. The constant R is the universal gas constant
and a and b are positive constants that are characteristic of a
particular gas.
(a) If T remains constant, use implicit differentiation to
find dVydP.
(b) Find the rate of change of volume with respect to
pressure of 1 mole of carbon dioxide at a volume of
V − 10 L and a pressure of P − 2.5 atm. Use
a − 3.592 L2-atmymole 2 and b − 0.04267 Lymole.
y±0
x − y3 1 y
y±0
Show that although the expressions you get for dyydx
look different, they agree for all points that satisfy the given
equation.
66. The Bessel function of order 0, y − J sxd, satisfies the differential equation xy99 1 y9 1 xy − 0 for all values of x and
its value at 0 is J s0d − 1.
(a) Find J9s0d.
(b) Use implicit differentiation to find J99s0d.
67. The figure shows a lamp located three units to the right of
the y-axis and a shadow created by the elliptical region
x 2 1 4y 2 < 5. If the point s25, 0d is on the edge of the
shadow, how far above the x-axis is the lamp located?
y
?
_5
0
≈+4¥=5
3
x
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.6
DISCOVERY PROJECT
Derivatives of Logarithmic and Inverse Trigonometric Functions
217
; FAMILIES OF IMPLICIT CURVES
In this project you will explore the changing shapes of implicitly defined curves as you vary
the constants in a family, and determine which features are common to all members of the
family.
1. Consider the family of curves
y 2 2 2x 2 sx 1 8d − c fs y 1 1d2 s y 1 9d 2 x 2 g
(a) By graphing the curves with c − 0 and c − 2, determine how many points of intersection there are. (You might have to zoom in to find all of them.)
(b) Now add the curves with c − 5 and c − 10 to your graphs in part (a). What do you
notice? What about other values of c ?
2. (a) Graph several members of the family of curves
x 2 1 y 2 1 cx 2 y 2 − 1
Describe how the graph changes as you change the value of c.
(b) What happens to the curve when c − 21? Describe what appears on the screen.
Can you prove it algebraically?
(c) Find y9 by implicit differentiation. For the case c − 21, is your expression for y9 consistent with what you discovered in part (b)?
3.6 Derivatives of Logarithmic and Inverse Trigonometric
Functions
In this section we use implicit differentiation to find derivatives of logarithmic functions
and of inverse trigonometric functions.
■ Derivatives of Logarithmic Functions
In Appendix F we prove that if f is a one-to-one differentiable function, then its inverse
function f 21 is also differentiable, except where its tangents are vertical. This is plausible because, geometrically, we can think of a differentiable function as one whose
graph has no corner or cusp. We obtain the graph of f 21 by reflecting the graph of f
about the line y − x, so the graph of f 21 has no corner or cusp either. (Note that if f has
a horizontal tangent at a point, then f 21 has a vertical tangent at the corresponding
reflected point and so f 21 is not differentiable there.)
Because the logarithmic function y − log b x is the inverse of the exponential function
y − b x, which we know is differentiable from Section 3.1, it follows that the logarithmic
function is also differentiable. We now state and prove the formula for the derivative of a
logarithmic function.
1
d
1
slog b xd −
dx
x ln b
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218
CHAPTER 3
Differentiation Rules
PROOF Let y − log b x. Then
by − x
Formula 3.4.5 says that
d
sb x d − b x ln b
dx
Differentiating this equation implicitly with respect to x, and using Formula 3.4.5,
we get
sb y ln bd
dy
−1
dx
dy
1
1
− y
−
dx
b ln b
x ln b
and so
n
If we put b − e in Formula 1, then the factor ln b on the right side becomes ln e − 1
and we get the formula for the derivative of the natural logarithmic function log e x − ln x :
d
1
sln xd −
dx
x
2
By comparing Formulas 1 and 2, we see one of the main reasons that natural logarithms (logarithms with base e) are used in calculus: the differentiation formula is simplest when b − e because ln e − 1.
EXAMPLE 1 Differentiate y − lnsx 3 1 1d.
SOLUTION To use the Chain Rule, we let u − x 3 1 1. Then y − ln u, so
dy
dy du
1 du
1
3x 2
−
−
− 3
s3x 2 d − 3
dx
du dx
u dx
x 11
x 11
n
In general, if we combine Formula 2 with the Chain Rule as in Example 1, we get
3
d
1 du
sln ud −
dx
u dx
EXAMPLE 2 Find
or
d
t9sxd
fln tsxdg −
dx
tsxd
d
lnssin xd.
dx
SOLUTION Using (3), we have
d
1 d
1
lnssin xd −
ssin xd −
cos x − cot x
dx
sin x dx
sin x
n
EXAMPLE 3 Differentiate f sxd − sln x .
SOLUTION This time the logarithm is the inner function, so the Chain Rule gives
f 9sxd − 12 sln xd21y2
1
1
d
1
! −
sln xd −
x
dx
2xsln
x
2sln x
n
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SECTION 3.6
Derivatives of Logarithmic and Inverse Trigonometric Functions
219
EXAMPLE 4 Differentiate f sxd − log 10 s2 1 sin xd.
SOLUTION Using Formula 1 with b − 10, we have
d
log 10 s2 1 sin xd
dx
1
d
−
s2 1 sin xd
s2 1 sin xd ln 10 dx
cos x
−
s2 1 sin xd ln 10
f 9sxd −
Figure 1 shows the graph of the function f of Example 5 together with the
graph of its derivative. It gives a visual
check on our calculation. Notice that
f 9sxd is large negative when f is
decreasing rapidly.
y
EXAMPLE 5 Find
d
x11
ln
.
dx
sx 2 2
SOLUTION 1
d x11
d
x11
1
ln
−
x 1 1 dx sx 2 2
dx
sx 2 2
sx 2 2
f
1
0
n
x
−
sx 2 2 sx 2 2 ∙ 1 2 sx 1 1d( 12 )sx 2 2d21y2
x11
x22
−
x 2 2 2 12 sx 1 1d
sx 1 1dsx 2 2d
−
x25
2sx 1 1dsx 2 2d
fª
SOLUTION 2 If we first expand the given function using the laws of logarithms, then
the differentiation becomes easier:
FIGURE 1
d
x11
d
ln
−
flnsx 1 1d 2 12 lnsx 2 2dg
dx
dx
sx 2 2
Figure 2 shows the graph of the function f sxd − ln x in Example 6 and
its derivative f 9sxd − 1yx. Notice
that when x is small, the graph of
y − ln x is steep and so f 9sxd is
large (positive or negative).
| |
| |
−
f sxd −
f
3
H
ln x
if x . 0
lns2xd if x , 0
it follows that
f 9sxd −
_3
FIGURE 2
1
x22
EXAMPLE 6 Find f 9sxd if f sxd − ln | x |.
fª
_3
S D
(This answer can be left as written, but if we used a common denominator we would
see that it gives the same answer as in Solution 1.)
n
SOLUTION Since
3
1
1
2
x11
2
1
if x . 0
x
1
1
s21d −
if x , 0
2x
x
Thus f 9sxd − 1yx for all x ± 0.
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n
220
CHAPTER 3
Differentiation Rules
The result of Example 6 is worth remembering:
d
1
ln x −
dx
x
| |
4
■ Logarithmic Differentiation
The calculation of derivatives of complicated functions involving products, quotients, or
powers can often be simplified by taking logarithms. The method used in the following
example is called logarithmic differentiation.
x 3y4 sx 2 1 1
.
s3x 1 2d5
SOLUTION We take logarithms of both sides of the equation and use the Laws of
Logarithms to simplify:
EXAMPLE 7 Differentiate y −
ln y − 34 ln x 1 12 lnsx 2 1 1d 2 5 lns3x 1 2d
Differentiating implicitly with respect to x gives
1 dy
3 1
1
2x
3
− ! 1 ! 2
25!
y dx
4 x
2 x 11
3x 1 2
Solving for dyydx, we get
S
dy
3
x
15
−y
1 2
2
dx
4x
x 11
3x 1 2
If we hadn’t used logarithmic differentiation in Example 7, we would have
had to use both the Quotient Rule
and the Product Rule. The resulting
calculation would have been
horrendous.
D
Because we have an explicit expression for y, we can substitute and write
dy
x 3y4 sx 2 1 1
−
dx
s3x 1 2d5
S
3
x
15
1 2
2
4x
x 11
3x 1 2
D
n
Steps in Logarithmic Differentiation
1. Take natural logarithms of both sides of an equation y − f sxd and use the Laws
of Logarithms to expand the expression.
2. Differentiate implicitly with respect to x.
3. Solve the resulting equation for y9 and replace y by f sxd.
If f sxd , 0 for some values of x, then ln f sxd is not defined, but we can still use logarithmic differentiation by first writing y − f sxd and then using Equation 4. We illustrate this procedure by proving the general version of the Power Rule, as promised in
Section 3.1. Recall that the general version of the Power Rule states that if n is any real
number and f sxd − x n, then f 9sxd − nx n21.
| | |
If x − 0, we can show that f 9s0d − 0
for n . 1 directly from the definition
of a derivative.
|
PROOF OF THE POWER RULE (GENERAL VERSION) Let y − x n and use logarithmic
differentiation:
ln y − ln x n − n ln x
x±0
| |
| |
y9
n
−
y
x
Therefore
Hence
| |
y9 − n
y
xn
−n
− nx n21
x
x
n
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SECTION 3.6
Derivatives of Logarithmic and Inverse Trigonometric Functions
221
You should distinguish carefully between the Power Rule fsx n d9 − nx n21 g, where
the base is variable and the exponent is constant, and the rule for differentiating exponential functions fsb x d9 − b x ln bg, where the base is constant and the exponent is
variable.
In general there are four cases for exponents and bases:
Constant base, constant exponent
1.
d
sb n d − 0
dx
Variable base, constant exponent
2.
d
f f sxdg n − nf f sxdg n21 f 9sxd
dx
Constant base, variable exponent
3.
d
fb tsxd g − b tsxdsln bdt9sxd
dx
Variable base, variable exponent
4. To find sdydxdf f sxdg tsxd, logarithmic differentiation can be used, as in the next
example.
(b and n are constants)
EXAMPLE 8 Differentiate y − x sx .
SOLUTION 1 Since both the base and the exponent are variable, we use logarithmic
differentiation:
Figure 3 illustrates Example 8 by
showing the graphs of f sxd − x sx and
its derivative.
y
S
y9 − y
1
sx
1
ln x
2 sx
D S
− x sx
2 1 ln x
2 sx
D
SOLUTION 2 Another method is to use Equation 1.5.10 to write x sx − e sx ln x :
1
FIGURE 3
y9
1
1
− sx ! 1 sln xd
y
x
2 sx
f
fª
0
ln y − ln x sx − sx ln x
1
x
d
d sx ln x
d
( x sx ) − dx
(e ) − e sx ln x dx
(sx ln x)
dx
− x sx
S
2 1 ln x
2 sx
D
(as in Solution 1)
n
■ The Number e as a Limit
We have shown that if f sxd − ln x, then f 9sxd − 1yx. Thus f 9s1d − 1. We now use this
fact to express the number e as a limit.
From the definition of a derivative as a limit, we have
f 9s1d − lim
hl0
− lim
xl0
f s1 1 hd 2 f s1d
f s1 1 xd 2 f s1d
− lim
xl0
h
x
lns1 1 xd 2 ln 1
1
− lim lns1 1 xd
xl0 x
x
− lim lns1 1 xd1yx
xl0
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222
CHAPTER 3
Differentiation Rules
y
Because f 9s1d − 1, we have
lim lns1 1 xd1yx − 1
3
2
xl0
y=(1+x)!?®
Then, by Theorem 2.5.8 and the continuity of the exponential function, we have
1 yx
e − e1 − e limx l 0 lns11xd
1
0
x
1 yx
− lim e lns11xd
xl0
− lim s1 1 xd1yx
xl0
e − lim s1 1 xd1yx
5
xl0
FIGURE 4
x
s1 1 xd 1yx
0.1
0.01
0.001
0.0001
0.00001
0.000001
0.0000001
0.00000001
2.59374246
2.70481383
2.71692393
2.71814593
2.71826824
2.71828047
2.71828169
2.71828181
Formula 5 is illustrated by the graph of the function y − s1 1 xd1yx in Figure 4 and a
table of values for small values of x. This illustrates the fact that, correct to seven decimal
places,
e < 2.7182818
If we put n − 1yx in Formula 5, then n l ` as x l 01 and so an alternative expression for e is
6
e − lim
nl`
S D
11
1
n
n
■ Derivatives of Inverse Trigonometric Functions
The inverse trigonometric functions were reviewed in Section 1.5. We discussed their
continuity in Section 2.5 and their asymptotes in Section 2.6. Here we use implicit
differentiation to find their derivatives. At the beginning of this section we observed
that if f is a one-to-one differentiable function, then its inverse function f 21 is also
differentiable (except where its tangents are vertical). Because the trigonometric
functions—with the restricted domains that we used to define their inverses—are oneto-one and differentiable, it follows that the inverse trigonometric functions are also
differentiable.
Recall the definition of the arcsine function:
!
!
y − sin21 x
means
sin y − x and 2 < y <
2
2
Differentiating sin y − x implicitly with respect to x, we obtain
cos y
dy
−1
dx
or
dy
1
−
dx
cos y
Now cos y > 0 because 2!y2 < y < !y2, so
cos y − s1 2 sin 2 y − s1 2 x 2
Therefore
scos2 y 1 sin2 y − 1d
dy
1
1
−
−
dx
cos y
s1 2 x 2
d
1
ssin21xd −
dx
s1 2 x 2
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SECTION 3.6
Figure 5 shows the graph of
f sxd − tan21x and its derivative
f 9sxd − 1ys1 1 x 2 d. Notice that f is
increasing and f 9sxd is always positive. The fact that tan21x l 6!y2 as
x l 6` is reflected in the fact that
f 9sxd l 0 as x l 6`.
sec2 y
_6
dy
−1
dx
dy
1
1
1
−
−
−
2
2
dx
sec y
1 1 tan y
1 1 x2
y=tan–!x
1
1+≈
d
1
stan21xd −
dx
1 1 x2
6
_1.5
223
The formula for the derivative of the arctangent function is derived in a similar way. If
y − tan21x, then tan y − x. Differentiating tan y − x implicitly with respect to x, we have
1.5
y=
Derivatives of Logarithmic and Inverse Trigonometric Functions
The inverse trigonometric functions sin21x and tan21x occur most frequently. The
derivatives of the remaining four are given in the following table. The proofs of the formulas are left as exercises.
FIGURE 5
Derivatives of Inverse Trigonometric Functions
d
1
ssin21xd −
dx
s1 2 x 2
d
1
scsc21xd − 2
dx
xsx 2 2 1
d
1
scos21xd − 2
dx
s1 2 x 2
d
1
ssec21xd −
dx
xsx 2 2 1
d
1
stan21xd −
dx
1 1 x2
d
1
scot21xd − 2
dx
1 1 x2
EXAMPLE 9 Differentiate (a) y −
1
and (b) f sxd − x arctansx .
sin21x
The formulas for the derivatives of
csc21x and sec21x depend on the definitions that are used for these functions. See Exercise 82.
SOLUTION
(a)
dy
d
d
−
ssin21xd21 − 2ssin21xd22
ssin21xd
dx
dx
dx
−2
Recall that arctan x is an alternative
notation for tan21x.
(b)
1
ssin21xd2s1 2 x 2
f 9sxd − x
−
1
1 1 (sx )
2
( 21 x21y2) 1 arctansx
sx
1 arctansx
2s1 1 xd
n
EXAMPLE 10 Differentiate tsxd − sec21sx 2 d.
SOLUTION
t9sxd −
1
x ssx d 2 1
2
2 2
s2xd −
2
x sx 4 2 1
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n
224
CHAPTER 3
3.6
Differentiation Rules
Exercises
1. Explain why the natural logarithmic function y − ln x is used
much more frequently in calculus than the other logarithmic
functions y − log b x.
2–26 Differentiate the function.
2. tstd − lns3 1 t d
3. f sxd − lnsx 2 1 3x 1 5d
4. f sxd − x ln x 2 x
5. f sxd − sinsln xd
6. f sxd − lnssin xd
2
1
x
8. y −
1
ln x
9. tsxd − lnsxe 22x d
10. tstd − s1 1 ln t
11. Fstd − sln td sin t
12. pstd − ln st 2 1 1
13. y − log8sx 1 3xd
14. y − log10 sec x
15. Fssd − ln ln s
ln v
16. Psvd −
12v
2
2
|
19. y − ln 3 2 2x
21. y − lnse
2x
23. hsxd − e
5
|
3
2t 2 1
s
20. y − lnscsc x 2 cot xd
22. tsxd − e x ln x
2
1 xe d
2x
Î
x 21ln x
24. y − ln
xa
bx
25. y − ln
tst 2 1 1d4
18. tstd − ln
17. T szd − 2 z log 2 z
39. y − lnsx 2 2 3x 1 1d, s3, 0d
40. y − x 2 ln x,
2
7. f sxd − ln
39–40 Find an equation of the tangent line to the curve at the
given point.
1 1 2x
1 2 2x
26. y − log 2 sx log 5 xd
s1, 0d
; 41. If f sxd − sin x 1 ln x, find f 9sxd. Check that your answer is
reasonable by comparing the graphs of f and f 9.
; 42. Find equations of the tangent lines to the curve y − sln xdyx
at the points s1, 0d and se, 1yed. Illustrate by graphing the
curve and its tangent lines.
43. Let f sxd − cx 1 lnscos xd. For what value of c is f 9s!y4d − 6?
44. Let f sxd − log b s3x 2 2 2d. For what value of b is f 9s1d − 3?
45–56 Use logarithmic differentiation to find the derivative of the
function.
45. y − sx 2 1 2d2sx 4 1 4d4
47. y −
Î
46. y −
x21
x4 1 1
e2x cos2 x
x2 1 x 1 1
48. y − sx e x 2x sx 1 1d2y3
2
49. y − x x
50. y − x 1yx
51. y − x sin x
52. y − (sx )
53. y − scos xd x
54. y − ssin xd ln x
55. y − x ln x
56. y − sln xdcos x
x
57. Find y9 if y − lnsx 2 1 y 2 d.
27. Show that
d
1
ln( x 1 sx 2 1 1 ) −
.
2 1 1
dx
sx
28. Show that
d
ln
dx
Î
1 2 cos x
− csc x .
1 1 cos x
|
31. y − ln sec x
30. y −
|
x
1 2 lnsx 2 1d
60. Find
d9
sx 8 ln xd.
dx 9
ln x
1 1 ln x
32. y − lns1 1 ln xd
lim
xl0
62. Show that lim
nl`
33–36 Differentiate f and find the domain of f .
33. f sxd −
59. Find a formula for f sndsxd if f sxd − lnsx 2 1d.
61. Use the definition of a derivative to prove that
29–32 Find y9 and y99.
29. y − sx ln x
58. Find y9 if x y − y x.
34. f sxd − s2 1 ln x
lns1 1 xd
−1
x
S D
11
x
n
n
− e x for any x . 0.
63–78 Find the derivative of the function. Simplify where
possible.
63. f sxd − sin21s5xd
64. tsxd − sec21se x d
65. y − tan21sx 2 1
66. y − tan21 sx 2 d
67. y − stan21 xd 2
68. tsxd − arccos sx
37. If f sxd − lnsx 1 ln xd, find f 9s1d.
69. hsxd − sarcsin xd ln x
70. tstd − lnsarctanst 4dd
38. If f sxd − cossln x 2 d, find f 9s1d.
71. f szd − e arcsinsz d
35. f sxd − lnsx 2 2 2xd
36. f sxd − ln ln ln x
2
72. y − tan21 s x 2 s1 1 x 2 d
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SECTION 3.7
73. hstd − cot21std 1 cot21s1ytd
Rates of Change in the Natural and Social Sciences
(b) Another way of defining sec21x that is sometimes used
is to say that y − sec21x &? sec y − x and
0 < y < !, y ± !y2. Show that, with this definition,
74. Rstd − arcsins1ytd
75. y − x sin21 x 1 s1 2 x 2
d
1
ssec21xd −
dx
x sx 2 2 1
| |
76. y − cos21ssin21 td
SD Î
Î
77. y − tan21
x
a
1 ln
83. Derivatives of Inverse Functions Suppose that f is a oneto-one differentiable function and its inverse function f 21 is
also differentiable. Use implicit differentiation to show that
x2a
x1a
12x
11x
78. y − arctan
225
s f 21d9sxd −
1
f 9s f 21sxdd
provided that the denominator is not 0.
; 79–80 Find f 9sxd. Check that your answer is reasonable by
comparing the graphs of f and f 9.
79. f sxd − s1 2 x 2 arcsin x
80. f sxd − arctansx 2 2 xd
81. Prove the formula for sdydxdscos21xd by the same method as
for sdydxdssin21xd.
84–86 Use the formula in Exercise 83.
84. If f s4d − 5 and f 9s4d − 23, find s f 21d9s5d.
85. If f sxd − x 1 e x, find s f 21d9s1d.
86. If f sxd − x 3 1 3 sin x 1 2 cos x, find s f 21d9s2d.
82. (a) One way of defining sec21x is to say that y − sec21x &?
sec y − x and 0 < y , !y2 or ! < y , 3!y2. Show
that, with this definition,
87. Suppose that f and t are differentiable functions and let
hsxd − f sxd tsxd. Use logarithmic differentiation to derive the
formula
h9 − t ? f t21 ? f 9 1 s ln f d ? f t ? t9
d
1
ssec21xd −
dx
x sx 2 2 1
88. Use the formula in Exercise 87 to find the derivative.
(a) hsxd − x 3
(b) hsxd − 3 x
(c) hsxd − ssin xd x
3.7 Rates of Change in the Natural and Social Sciences
We know that if y − f sxd, then the derivative dyydx can be interpreted as the rate of
change of y with respect to x. In this section we examine some of the applications of this
idea to physics, chemistry, biology, economics, and other sciences.
Let’s recall from Section 2.7 the basic idea behind rates of change. If x changes from
x 1 to x 2, then the change in x is
Dx − x 2 2 x 1
and the corresponding change in y is
y
Dy − f sx 2 d 2 f sx 1 d
Q {x™, ‡}
The difference quotient
Dy
f sx 2 d 2 f sx 1 d
−
Dx
x2 2 x1
Îy
P { ⁄, fl}
Îx
0
⁄
x™
mPQ ! average rate of change
m=fª(⁄)=instantaneous rate
of change
FIGURE 1
x
is the average rate of change of y with respect to x over the interval fx 1, x 2 g and can be
interpreted as the slope of the secant line PQ in Figure 1. Its limit as Dx l 0 is the derivative f 9sx 1 d, which can therefore be interpreted as the instantaneous rate of change of y
with respect to x or the slope of the tangent line at Psx 1, f sx 1 dd. Using Leibniz notation,
we write the process in the form
dy
Dy
− lim
Dx l 0 Dx
dx
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226
CHAPTER 3
Differentiation Rules
Whenever the function y − f sxd has a specific interpretation in one of the sciences, its
derivative will have a specific interpretation as a rate of change. (As we discussed in Section 2.7, the units for dyydx are the units for y divided by the units for x.) We now look
at some of these interpretations in the natural and social sciences.
■ Physics
If s − f std is the position function of a particle that is moving in a straight line, then
DsyDt represents the average velocity over a time period Dt, and v − dsydt represents
the instantaneous velocity (the rate of change of displacement with respect to time).
The instantaneous rate of change of velocity with respect to time is acceleration:
astd − v9std − s99std. This was discussed in Sections 2.7 and 2.8, but now that we know
the differentiation formulas, we are able to more easily solve problems involving the
motion of objects.
EXAMPLE 1 The position of a particle is given by the equation
s − f std − t 3 2 6t 2 1 9t
where t is measured in seconds and s in meters.
(a) Find the velocity at time t.
(b) What is the velocity after 2 s? After 4 s?
(c) When is the particle at rest?
(d) When is the particle moving forward (that is, in the positive direction)?
(e) Draw a diagram to represent the motion of the particle.
(f ) Find the total distance traveled by the particle during the first five seconds.
(g) Find the acceleration at time t and after 4 s.
(h) Graph the position, velocity, and acceleration functions for 0 < t < 5.
(i) When is the particle speeding up? When is it slowing down?
SOLUTION
(a) The velocity function is the derivative of the position function:
s − f std − t 3 2 6t 2 1 9t
vstd −
ds
− 3t 2 2 12t 1 9
dt
(b) The velocity after 2 s means the instantaneous velocity when t − 2, that is,
v s2d −
ds
dt
Z
t−2
− 3s2d2 2 12s2d 1 9 − 23 mys
The velocity after 4 s is
v s4d − 3s4d2 2 12s4d 1 9 − 9 mys
(c) The particle is at rest when v std − 0, that is,
3t 2 2 12t 1 9 − 3st 2 2 4t 1 3d − 3st 2 1dst 2 3d − 0
and this is true when t − 1 or t − 3. Thus the particle is at rest after 1 s and after 3 s.
(d) The particle moves in the positive direction when v std . 0, that is,
3t 2 2 12t 1 9 − 3st 2 1dst 2 3d . 0
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SECTION 3.7
Rates of Change in the Natural and Social Sciences
227
This inequality is true when both factors are positive st . 3d or when both factors are
negative st , 1d. Thus the particle moves in the positive direction in the time intervals
t , 1 and t . 3. It moves backward (in the negative direction) when 1 , t , 3.
t=3
s=0
t=0
s=0
s
t=1
s=4
(e) Using the information from part (d) we make a schematic sketch in Figure 2 of the
motion of the particle back and forth along a line (the s-axis).
(f ) Because of what we learned in parts (d) and (e), we need to calculate the distances
traveled during the time intervals [0, 1], [1, 3], and [3, 5] separately.
The distance traveled in the first second is
| f s1d 2 f s0d | − | 4 2 0 | − 4 m
FIGURE 2
From t − 1 to t − 3 the distance traveled is
| f s3d 2 f s1d | − | 0 2 4 | − 4 m
From t − 3 to t − 5 the distance traveled is
| f s5d 2 f s3d | − | 20 2 0 | − 20 m
25
√
0
s
The total distance is 4 1 4 1 20 − 28 m.
(g) The acceleration is the derivative of the velocity function:
a
5
astd −
d 2s
dv
−
− 6t 2 12
dt 2
dt
as4d − 6s4d 2 12 − 12 mys 2
_12
FIGURE 3
(h) Figure 3 shows the graphs of s, v, and a.
( i) The particle speeds up when the velocity is positive and increasing (v and a are
both positive) and also when the velocity is negative and decreasing (v and a are both
negative). In other words, the particle speeds up when the velocity and acceleration
have the same sign. (The particle is pushed in the same direction it is moving.) From
Figure 3 we see that this happens when 1 , t , 2 and when t . 3. The particle slows
down when v and a have opposite signs, that is, when 0 < t , 1 and when 2 , t , 3.
Figure 4 summarizes the motion of the particle.
5
0
_5
s
t
1
forward
FIGURE 4
a
√
slows
down
backward
speeds
up
slows
down
forward
speeds
up
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228
CHAPTER 3
Differentiation Rules
EXAMPLE 2 If a rod or piece of wire is homogeneous, then its linear density is
uniform and is defined as the mass per unit length s' − myld and measured in
kilograms per meter. Suppose, however, that the rod is not homogeneous but that its
mass measured from its left end to a point x is m − f sxd, as shown in Figure 5.
x
FIGURE 5
x¡
This part of the rod has mass ƒ.
x™
The mass of the part of the rod that lies between x − x 1 and x − x 2 is given by
Dm − f sx 2 d 2 f sx 1 d, so the average density of that part of the rod is
average density −
Dm
f sx 2 d 2 f sx 1 d
−
Dx
x2 2 x1
If we now let Dx l 0 (that is, x 2 l x 1), we are computing the average density over
smaller and smaller intervals. The linear density ' at x 1 is the limit of these average
densities as Dx l 0 ; that is, the linear density is the rate of change of mass with
respect to length. Symbolically,
Dm
dm
−
Dx l 0 Dx
dx
' − lim
Thus the linear density of the rod is the derivative of mass with respect to length.
For instance, if m − f sxd − sx , where x is measured in meters and m in kilograms,
then the average density of the part of the rod given by 1 < x < 1.2 is
Dm
f s1.2d 2 f s1d
s1.2 2 1
−
−
< 0.48 kgym
Dx
1.2 2 1
0.2
while the density right at x − 1 is
'−
!
!
!
!
FIGURE 6
!
!
!
dm
dx
Z
x−1
−
1
2sx
Z
x−1
− 0.50 kgym
n
EXAMPLE 3 A current exists whenever electric charges move. Figure 6 shows part
of a wire and electrons moving through a plane surface, shaded red. If DQ is the net
charge that passes through this surface during a time period Dt, then the average
current during this time interval is defined as
average current −
DQ
Q2 2 Q1
−
Dt
t2 2 t1
If we take the limit of this average current over smaller and smaller time intervals,
we get what is called the current I at a given time t1:
DQ
dQ
−
Dt l 0 Dt
dt
I − lim
Thus the current is the rate at which charge flows through a surface. It is measured in
units of charge per unit time (often coulombs per second, called amperes).
n
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SECTION 3.7
Rates of Change in the Natural and Social Sciences
229
Velocity, density, and current are not the only rates of change that are important in
physics. Others include power (the rate at which work is done), the rate of heat flow,
temperature gradient (the rate of change of temperature with respect to position), and the
rate of decay of a radioactive substance in nuclear physics.
■ Chemistry
EXAMPLE 4 A chemical reaction results in the formation of one or more substances
(called products) from one or more starting materials (called reactants). For instance,
the “equation”
2H2 1 O2 l 2H2 O
indicates that two molecules of hydrogen and one molecule of oxygen form two
molecules of water. Let’s consider the reaction
A1BlC
where A and B are the reactants and C is the product. The concentration of a reactant A
is the number of moles (1 mole − 6.022 3 10 23 molecules) per liter and is denoted by
fAg. The concentration varies during a reaction, so fAg, fBg, and fCg are all functions of
time std. The average rate of reaction of the product C over a time interval t1 < t < t2 is
DfCg
fCgst2 d 2 fCgst1 d
−
Dt
t2 2 t1
But chemists are interested in the instantaneous rate of reaction because it gives
information about the mechanism of the chemical reaction. The instantaneous rate of
reaction is obtained by taking the limit of the average rate of reaction as the time
interval Dt approaches 0 :
rate of reaction − lim
Dt l 0
DfCg
dfCg
−
Dt
dt
Since the concentration of the product increases as the reaction proceeds, the derivative
dfCg ydt will be positive, and so the rate of reaction of C is positive. The concentrations
of the reactants, however, decrease during the reaction, so, to make the rates of reaction
of A and B positive numbers, we put minus signs in front of the derivatives dfAg ydt
and dfBg ydt. Since fAg and fBg each decrease at the same rate that fCg increases, we
have
rate of reaction −
dfCg
dfAg
dfBg
−2
−2
dt
dt
dt
More generally, it turns out that for a reaction of the form
aA 1 bB l cC 1 dD
we have
2
1 dfAg
1 dfBg
1 dfCg
1 dfDg
−2
−
−
a dt
b dt
c dt
d dt
The rate of reaction can be determined from data and graphical methods. In some cases
there are explicit formulas for the concentrations as functions of time that enable us to
compute the rate of reaction (see Exercise 26).
n
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230
CHAPTER 3
Differentiation Rules
EXAMPLE 5 One of the quantities of interest in thermodynamics is compressibility. If
a given substance is kept at a constant temperature, then its volume V depends on its
pressure P. We can consider the rate of change of volume with respect to pressure—
namely, the derivative dVydP. As P increases, V decreases, so dVydP , 0. The compressibility is defined by introducing a minus sign and dividing this derivative by the
volume V:
isothermal compressibility − ( − 2
1 dV
V dP
Thus ( measures how fast, per unit volume, the volume of a substance decreases as the
pressure on it increases at constant temperature.
For instance, the volume V (in cubic meters) of a sample of air at 258C was found to
be related to the pressure P (in kilopascals) by the equation
V−
5.3
P
The rate of change of V with respect to P when P − 50 kPa is
dV
dP
Z
P−50
Z
−2
5.3
P2
−2
5.3
− 20.00212 m 3ykPa
2500
P−50
The compressibility at that pressure is
(−2
1 dV
V dP
Z
P−50
−
0.00212
− 0.02 sm 3ykPadym 3
5.3
50
n
■ Biology
EXAMPLE 6 Let n − f std be the number of individuals in an animal or plant population at time t. The change in the population size between the times t − t1 and t − t2
is Dn − f st2 d 2 f st1 d, and so the average rate of growth during the time period
t1 < t < t2 is
average rate of growth −
Dn
f st2 d 2 f st1 d
−
Dt
t2 2 t1
The instantaneous rate of growth is obtained from this average rate of growth by
letting the time period Dt approach 0:
growth rate − lim
Dt l 0
Dn
dn
−
Dt
dt
Strictly speaking, this is not quite accurate because the actual graph of a population function n − f std would be a step function that is discontinuous whenever a
birth or death occurs and therefore not differentiable. However, for a large animal
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SECTION 3.7
Rates of Change in the Natural and Social Sciences
231
or plant population, we can replace the graph by a smooth approximating curve as
in Figure 7.
n
FIGURE 7
A smooth curve approximating
a growth function
0
t
To be more specific, consider a population of bacteria in a homogeneous nutrient
medium. Suppose that by sampling the population at certain intervals it is determined
that the population doubles every hour. If the initial population is n0 and the time t is
measured in hours, then
f s1d − 2f s0d − 2n0
f s2d − 2f s1d − 2 2n0
Science Photo Library / Alamy Stock Photo
f s3d − 2f s2d − 2 3n0
and, in general,
f std − 2 t n0
The population function is n − n0 2 t.
In Section 3.4 we showed that
E. coli bacteria measure about
2 micrometers (mm) long and
0.75 mm wide. The image was
produced with a scanning electron
microscope.
d
sb x d − b x ln b
dx
So the rate of growth of the bacteria population at time t is
dn
d
−
sn0 2t d − n0 2t ln 2
dt
dt
For example, suppose that we start with an initial population of n0 − 100 bacteria.
Then the rate of growth after 4 hours is
dn
dt
Z
t−4
− 100 ! 24 ln 2 − 1600 ln 2 < 1109
This means that, after 4 hours, the bacteria population is growing at a rate of about
1109 bacteria per hour.
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232
CHAPTER 3
Differentiation Rules
EXAMPLE 7 When we consider the flow of blood through a blood vessel, such as a
vein or artery, we can model the shape of the blood vessel by a cylindrical tube with
radius R and length l as illustrated in Figure 8.
R
r
FIGURE 8
Blood flow in an artery
l
Because of friction at the walls of the tube, the velocity v of the blood is greatest
along the central axis of the tube and decreases as the distance r from the axis increases
until v becomes 0 at the wall. The relationship between v and r is given by the law of
laminar flow, which was experimentally derived by the French physicist Jean Léonard
Marie Poiseuille in 1838. This law states that
1
For more detailed information,
see W. Nichols, M. O’Rourke, and
C. Vlachopoulos (eds.), McDonald’s
Blood Flow in Arteries: Theoretical,
Experimental, and Clinical Principles,
6th ed. (Boca Raton, FL, 2011).
v−
P
sR 2 2 r 2 d
4)l
where ) is the viscosity of the blood and P is the pressure difference between the ends
of the tube. If P and l are constant, then v is a function of r with domain f0, Rg.
The average rate of change of the velocity as we move from r − r1 outward to
r − r2 is given by
Dv
vsr2 d 2 vsr1 d
−
Dr
r2 2 r1
and if we let Dr l 0, we obtain the velocity gradient, that is, the instantaneous rate of
change of velocity with respect to r :
velocity gradient − lim
Dv
Dr l 0 Dr
−
dv
dr
Using Equation 1, we obtain
dv
P
Pr
−
s0 2 2rd − 2
dr
4)l
2)l
For one of the smaller human arteries we can take ) − 0.027, R − 0.008 cm,
l − 2 cm, and P − 4000 dynesycm2, which gives
v−
4000
s0.000064 2 r 2 d
4s0.027d2
< 1.85 3 10 4s6.4 3 10 25 2 r 2 d
At r − 0.002 cm the blood is flowing at a speed of
vs0.002d < 1.85 3 10 4s64 3 1026 2 4 3 10 26 d − 1.11 cmys
and the velocity gradient at that point is
dv
dr
Z
r−0.002
−2
4000s0.002d
< 274 scmysdycm
2s0.027d2
To get a feeling for what this statement means, let’s change our units from centimeters
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SECTION 3.7
Rates of Change in the Natural and Social Sciences
233
to micrometers (1 cm − 10,000 !m). Then the radius of the artery is 80 !m. The
velocity at the central axis is 11,850 !mys, which decreases to 11,110 !mys at a
distance of r − 20 !m. The fact that dvydr − 274 (!mys)y!m means that, when
r − 20 !m, the velocity is decreasing at a rate of about 74 !mys for each micrometer
that we proceed away from the center.
n
■ Economics
EXAMPLE 8 Suppose Csxd is the total cost that a company incurs in producing
x units of a certain commodity. The function C is called a cost function. If the
number of items produced is increased from x 1 to x 2, then the additional cost is
DC − Csx 2 d 2 Csx 1 d, and the average rate of change of the cost is
DC
Csx 2 d 2 Csx 1 d
Csx 1 1 Dxd 2 Csx 1 d
−
−
Dx
x2 2 x1
Dx
The limit of this quantity as Dx l 0, that is, the instantaneous rate of change of
cost with respect to the number of items produced, is called the marginal cost by
economists:
marginal cost − lim
Dx l 0
DC
dC
−
Dx
dx
[Since x often takes on only integer values, it may not make literal sense to let Dx
approach 0, but we can always replace Csxd by a smooth approximating function as in
Example 6.]
Taking Dx − 1 and n large (so that Dx is small compared to n), we have
C9snd < Csn 1 1d 2 Csnd
Thus the marginal cost of producing n units is approximately equal to the cost of
producing one more unit [the sn 1 1dst unit].
It is often appropriate to represent a total cost function by a polynomial
Csxd − a 1 bx 1 cx 2 1 dx 3
where a represents the overhead cost (rent, heat, maintenance) and the other terms
represent the cost of raw materials, labor, and so on. (The cost of raw materials may be
proportional to x, but labor costs might depend partly on higher powers of x because of
overtime costs and inefficiencies involved in large-scale operations.)
For instance, suppose a company has estimated that the cost (in dollars) of producing x items is
Csxd − 10,000 1 5x 1 0.01x 2
Then the marginal cost function is
C9sxd − 5 1 0.02x
The marginal cost at the production level of 500 items is
C9s500d − 5 1 0.02s500d − $15yitem
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234
CHAPTER 3
Differentiation Rules
This gives the rate at which costs are increasing with respect to the production level
when x − 500 and predicts the cost of the 501st item.
The actual cost of producing the 501st item is
Cs501d 2 Cs500d − f10,000 1 5s501d 1 0.01s501d2 g
− 2 f10,000 1 5s500d 1 0.01s500d2 g
− $15.01
Notice that C9s500d < Cs501d 2 Cs500d.
n
Economists also study marginal demand, marginal revenue, and marginal profit, the
derivatives of the demand, revenue, and profit functions. These will be considered in
Chapter 4 after we have developed techniques for finding the maximum and minimum
values of functions.
■ Other Sciences
Rates of change occur in all the sciences. A geologist is interested in knowing the
rate at which an intruded body of molten rock cools by conduction of heat into surrounding rocks. An engineer wants to know the rate at which water flows out of a
reservoir. An urban geographer is interested in the rate of change of the population
density in a city as the distance from the city center increases. A meteorologist is
concerned with the rate of change of atmospheric pressure with respect to height (see
Exercise 3.8.19).
In psychology, those interested in learning theory study the learning curve, which
graphs the performance Pstd of someone learning a skill as a function of the training
time t. Of particular interest is the rate at which performance improves as time passes,
that is, dPydt. Psychologists have also studied the phenomenon of memory and have
developed models for the rate of memory retention (see Exercise 42). They also study the
difficulty involved in performing certain tasks and the rate at which difficulty increases
when a given parameter is changed (see Exercise 43).
In sociology, differential calculus is used in analyzing the spread of rumors (or innovations or fads or fashions). If pstd denotes the proportion of a population that knows a
rumor by time t, then the derivative dpydt represents the rate of spread of the rumor (see
Exercise 3.4.90).
■ A Single Idea, Many Interpretations
Velocity, density, current, power, and temperature gradient in physics; rate of reaction
and compressibility in chemistry; rate of growth and blood velocity gradient in biology;
marginal cost and marginal profit in economics; rate of heat flow in geology; rate of
improvement of performance in psychology; rate of spread of a rumor in sociology—
these are all special cases of a single mathematical concept, the derivative.
All of these different applications of the derivative illustrate the fact that part of the
power of mathematics lies in its abstractness. A single abstract mathematical concept
(such as the derivative) can have different interpretations in each of the sciences. When
we develop the properties of the mathematical concept once and for all, we can then turn
around and apply these results to all of the sciences. This is much more efficient than
developing properties of special concepts in each separate science. The French mathematician Joseph Fourier (1768–1830) put it succinctly: “Mathematics compares the most
diverse phenomena and discovers the secret analogies that unite them.”
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SECTION 3.7
Rates of Change in the Natural and Social Sciences
235
3.7 Exercises
1–4 A particle moves according to a law of motion s − f std,
t > 0, where t is measured in seconds and s in feet.
(a) Find the velocity at time t.
(b) What is the velocity after 1 second?
(c) When is the particle at rest?
(d) When is the particle moving in the positive direction?
(e) Find the total distance traveled during the first 6 seconds.
(f ) Draw a diagram like Figure 2 to illustrate the motion of the
particle.
(g) Find the acceleration at time t and after 1 second.
; (h) Graph the position, velocity, and acceleration functions
for 0 < t < 6.
(i) When is the particle speeding up? When is it slowing
down?
9t
t2 1 9
1. f std − t 3 2 9t 2 1 24t
2. f std −
3. f std − sins!ty2d
4. f std − t 2e 2t
5. Graphs of the velocity functions of two particles are shown,
where t is measured in seconds. When is each particle
speeding up? When is it slowing down? Explain.
(a)
√√
00
(b) √ √
11
tt
00
11
tt
6. Graphs of the position functions of two particles are
shown, where t is measured in seconds. When is the
velocity of each particle positive? When is it negative?
When is each particle speeding up? When is it slowing
down? Explain.
(a)
s s
00 1 1
00 1 1
1
0
1
x
8. For the particle described in Exercise 7, sketch a graph of
the acceleration function. When is the particle speeding up?
When is it slowing down? When is it traveling at a constant
speed?
9. The height (in meters) of a projectile shot vertically upward
from a point 2 m above ground level with an initial velocity
of 24.5 mys is h − 2 1 24.5t 2 4.9t 2 after t seconds.
(a) Find the velocity after 2 s and after 4 s.
(b) When does the projectile reach its maximum height?
(c) What is the maximum height?
(d) When does it hit the ground?
(e) With what velocity does it hit the ground?
10. If a ball is thrown vertically upward with a velocity of
80 ftys, then its height after t seconds is s − 80t 2 16t 2.
(a) What is the maximum height reached by the ball?
(b) What is the velocity of the ball when it is 96 ft above
the ground on its way up? On its way down?
11. If a rock is thrown vertically upward from the surface
of Mars with velocity 15 mys, its height after t seconds
is h − 15t 2 1.86t 2.
(a) What is the velocity of the rock after 2 s?
(b) What is the velocity of the rock when its height is 25 m
on its way up? On its way down?
12. A particle moves with position function
s − t 4 2 4t 3 2 20t 2 1 20t
t>0
(a) At what time does the particle have a velocity of 20 mys?
(b) At what time is the acceleration 0? What is the
significance of this value of t ?
(b) s s
t t
y
t t
7. Suppose that the graph of the velocity function of a particle
is as shown in the figure, where t is measured in seconds.
When is the particle traveling forward (in the positive direction)? When is it traveling backward? What is happening
when 5 , t , 7 ?
13. (a) A company makes computer chips from square wafers
of silicon. A process engineer wants to keep the side
length of a wafer very close to 15 mm and needs to
know how the area Asxd of a wafer changes when the
side length x changes. Find A9s15d and explain its
meaning in this situation.
(b) Show that the rate of change of the area of a square
with respect to its side length is half its perimeter. Try
to explain geometrically why this is true by drawing a
square whose side length x is increased by an amount
Dx. How can you approximate the resulting change in
area DA if Dx is small?
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236
CHAPTER 3
Differentiation Rules
14. (a) Sodium chlorate crystals are easy to grow in the shape of
cubes by allowing a solution of water and sodium chlorate to evaporate slowly. If V is the volume of such a cube
with side length x, calculate dVydx when x − 3 mm and
explain its meaning.
(b) Show that the rate of change of the volume of a cube with
respect to its edge length is equal to half the surface area
of the cube. Explain geometrically why this result is true
by arguing by analogy with Exercise 13(b).
15. (a) Find the average rate of change of the area of a circle
with respect to its radius r as r changes from
(i) 2 to 3
(ii) 2 to 2.5
(iii) 2 to 2.1
(b) Find the instantaneous rate of change when r − 2.
(c) Show that the rate of change of the area of a circle with
respect to its radius (at any r) is equal to the circumference of the circle. Try to explain geometrically why this
is true by drawing a circle whose radius is increased by
an amount Dr. How can you approximate the resulting
change in area DA if Dr is small?
16. A stone is dropped into a lake, creating a circular ripple that
travels outward at a speed of 60 cmys. Find the rate at which
the area within the circle is increasing after (a) 1 s, (b) 3 s,
and (c) 5 s. What can you conclude?
17. A spherical balloon is being inflated. Find the rate of increase
of the surface area sS − 4!r 2 d with respect to the radius r
when r is (a) 1 ft, (b) 2 ft, and (c) 3 ft. What conclusion can
you make?
18. (a) The volume of a growing spherical cell is V − 43 !r 3,
where the radius r is measured in micrometers
(1 μm − 1026 m). Find the average rate of change of V
with respect to r when r changes from
(i) 5 to 8 μm
(ii) 5 to 6 μm
(iii) 5 to 5.1 μm
(b) Find the instantaneous rate of change of V with respect
to r when r − 5 μm.
(c) Show that the rate of change of the volume of a sphere
with respect to its radius is equal to its surface area.
Explain geometrically why this result is true. Argue by
analogy with Exercise 15(c).
19. The mass of the part of a metal rod that lies between its left
end and a point x meters to the right is 3x 2 kg. Find the linear
density (see Example 2) when x is (a) 1 m, (b) 2 m, and
(c) 3 m. Where is the density the highest? The lowest?
20. If a cylindrical water tank holds 5000 gallons, and the water
drains from the bottom of the tank in 40 minutes, then
Torricelli’s Law gives the volume V of water remaining in
the tank after t minutes as
1
V − 5000 (1 2 40
t)
2
0 < t < 40
Find the rate at which water is draining from the tank after
(a) 5 min, (b) 10 min, (c) 20 min, and (d) 40 min. At what
time is the water flowing out the fastest? The slowest? Summarize your findings.
21. The quantity of charge Q in coulombs (C) that has passed
through a point in a wire up to time t (measured in seconds) is
given by Qstd − t 3 2 2t 2 1 6t 1 2. Find the current when
(a) t − 0.5 s and (b) t − 1 s. (See Example 3. The unit of current is an ampere [1 A − 1 Cys].) At what time is the current
lowest?
22. Newton’s Law of Gravitation says that the magnitude F of the
force exerted by a body of mass m on a body of mass M is
F−
GmM
r2
where G is the gravitational constant and r is the distance
between the bodies.
(a) Find dFydr and explain its meaning. What does the minus
sign indicate?
(b) Suppose it is known that the earth attracts an object with
a force that decreases at the rate of 2 Nykm when
r − 20,000 km. How fast does this force change
when r − 10,000 km?
23. The force F acting on a body with mass m and velocity v is
the rate of change of momentum: F − sdydtd smvd. If m is
constant, this becomes F − ma, where a − dvydt is the
acceleration. But in the theory of relativity, the mass of a
particle varies with v as follows: m − m 0 ys1 2 v 2yc 2 where
m 0 is the mass of the particle at rest and c is the speed of
light. Show that
m0a
F−
s1 2 v 2yc 2 d3y2
24. Some of the highest tides in the world occur in the Bay of
Fundy on the Atlantic Coast of Canada. At Hopewell Cape
the water depth at low tide is about 2.0 m and at high tide it is
about 12.0 m. The natural period of oscillation is a little more
than 12 hours and on a day in June, high tide occurred at
6:45 am. This helps explain the following model for the water
depth D (in meters) as a function of the time t (in hours after
midnight) on that day:
Dstd − 7 1 5 cosf0.503st 2 6.75dg
How fast was the tide rising (or falling) at the following
times?
(a) 3:00 am
(b) 6:00 am
(c) 9:00 am
(d) Noon
25. Boyle’s Law states that when a sample of gas is compressed
at a constant temperature, the product of the pressure and the
volume remains constant: PV − C.
(a) Find the rate of change of volume with respect to
pressure.
(b) A sample of gas is in a container at low pressure and
is steadily compressed at constant temperature for
10 minutes. Is the volume decreasing more rapidly at
the beginning or the end of the 10 minutes? Explain.
(c) Prove that the isothermal compressibility (see
Example 5) is given by ( − 1yP.
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SECTION 3.7
26. If, in Example 4, one molecule of the product C is formed
from one molecule of the reactant A and one molecule of
the reactant B, and the initial concentrations of A and B
have a common value fAg − fBg − a molesyL, then
fCg − a 2ktysakt 1 1d
where k is a constant.
(a) Find the rate of reaction at time t.
(b) Show that if x − fCg, then
dx
− ksa 2 xd 2
dt
(c) What happens to the concentration as t l `?
(d) What happens to the rate of reaction as t l `?
(e) What do the results of parts (c) and (d) mean in
practical terms?
27. In Example 6 we considered a bacteria population that
doubles every hour. Suppose that another population of bacteria triples every hour and starts with 400 bacteria. Find an
expression for the number n of bacteria after t hours and use
it to estimate the rate of growth of the bacteria population
after 2.5 hours.
28. The number of yeast cells in a laboratory culture increases
rapidly initially but levels off eventually. The population is
modeled by the function
a
n − f std −
1 1 be20.7t
where t is measured in hours. At time t − 0 the population
is 20 cells and is increasing at a rate of 12 cellsyhour. Find
the values of a and b. According to this model, what happens to the yeast population in the long run?
29. The table gives the world population Pstd, in millions,
where t is measured in years and t − 0 corresponds to the
year 1900.
t
Population
(millions)
t
Population
(millions)
0
10
20
30
40
50
1650
1750
1860
2070
2300
2560
60
70
80
90
100
110
3040
3710
4450
5280
6080
6870
(a) Estimate the rate of population growth in 1920 and in
1980 by averaging the slopes of two secant lines.
(b) Use a graphing calculator or computer to find a cubic
function (a third-degree polynomial) that models the
data.
(c) Use your model in part (b) to find a model for the rate
of population growth.
(d) Use part (c) to estimate the rates of growth in 1920
and 1980. Compare with your estimates in part (a).
Rates of Change in the Natural and Social Sciences
237
(e) In Section 1.1 we modeled Pstd with the exponential
function
f std − s1.43653 3 10 9 d ! s1.01395d t
Use this model to find a model for the rate of population growth.
(f ) Use your model in part (e) to estimate the rate of
growth in 1920 and 1980. Compare with your estimates
in parts (a) and (d).
(g) Estimate the rate of growth in 1985.
30. The table shows how the average age of first marriage of
Japanese women has varied since 1950.
t
Astd
t
Astd
1950
1955
1960
1965
1970
1975
1980
23.0
23.8
24.4
24.5
24.2
24.7
25.2
1985
1990
1995
2000
2005
2010
2015
25.5
25.9
26.3
27.0
28.0
28.8
29.4
(a) Use a graphing calculator or computer to model these
data with a fourth-degree polynomial.
(b) Use part (a) to find a model for A9std.
(c) Estimate the rate of change of marriage age for women
in 1990.
(d) Graph the data points and the models for A and A9.
31. Refer to the law of laminar flow given in Example 7. Consider a blood vessel with radius 0.01 cm, length 3 cm, pressure difference 3000 dynesycm2, and viscosity ) − 0.027.
(a) Find the velocity of the blood along the centerline
r − 0, at radius r − 0.005 cm, and at the wall
r − R − 0.01 cm.
(b) Find the velocity gradient at r − 0, r − 0.005,
and r − 0.01.
(c) Where is the velocity the greatest? Where is the velocity
changing most?
32. The frequency of vibrations of a vibrating violin string is
given by
1
T
f−
2L
'
Î
where L is the length of the string, T is its tension, and ' is
its linear density. [See Chapter 11 in D. E. Hall, Musical
Acoustics, 3rd ed. (Pacific Grove, CA, 2002).]
(a) Find the rate of change of the frequency with respect to
(i) the length (when T and ' are constant),
(ii) the tension (when L and ' are constant), and
(iii) the linear density (when L and T are constant).
(b) The pitch of a note (how high or low the note sounds)
is determined by the frequency f . (The higher the
frequency, the higher the pitch.) Use the signs of the
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238
CHAPTER 3
Differentiation Rules
derivatives in part (a) to determine what happens to the
pitch of a note
(i) when the effective length of a string is decreased
by placing a finger on the string so a shorter portion of the string vibrates,
(ii) when the tension is increased by turning a tuning
peg,
(iii) when the linear density is increased by switching
to another string.
33. Suppose that the cost (in dollars) for a company to produce
x pairs of a new line of jeans is
Csxd − 2000 1 3x 1 0.01x 2 1 0.0002x 3
(a) Find the marginal cost function.
(b) Find C9s100d and explain its meaning. What does it
predict?
(c) Compare C9s100d with the cost of manufacturing the
101st pair of jeans.
34. The cost function for a certain commodity is
Csqd − 84 1 0.16q 2 0.0006q 2 1 0.000003q 3
(a) Find and interpret C9s100d.
(b) Compare C9s100d with the cost of producing the 101st
item.
35. If psxd is the total value of the production when there are
x workers in a plant, then the average productivity of the
workforce at the plant is
Asxd −
psxd
x
(a) Find A9sxd. Why does the company want to hire more
workers if A9sxd . 0 ?
(b) Show that A9sxd . 0 if p9sxd is greater than the average
productivity.
36. If R denotes the reaction of the body to some stimulus of
strength x, the sensitivity S is defined to be the rate of change
of the reaction with respect to x. A particular example is that
when the brightness x of a light source is increased, the eye
reacts by decreasing the area R of the pupil. The experimental formula
R−
;
40 1 24x 0.4
1 1 4x 0.4
has been used to model the dependence of R on x when R is
measured in square millimeters and x is measured in appropriate units of brightness.
(a) Find the sensitivity.
(b) Illustrate part (a) by graphing both R and S as functions
of x. Comment on the values of R and S at low levels of
brightness. Is this what you would expect?
37. Patients undergo dialysis treatment to remove urea from
their blood when their kidneys are not functioning properly.
Blood is diverted from the patient through a machine that
filters out urea. Under certain conditions, the duration of
dialysis required, given that the initial urea concentration is
c . 1, is given by the equation
S
t − ln
3c 1 s9c 2 2 8c
2
D
Calculate the derivative of t with respect to c and interpret it.
38. Invasive species often display a wave of advance as
they colonize new areas. Mathematical models based on
random dispersal and reproduction have demonstrated that
the speed with which such waves move is given by the
function f srd − 2 sDr , where r is the reproductive rate
of individuals and D is a parameter quantifying dispersal.
Calculate the derivative of the wave speed with respect to
the reproductive rate r and explain its meaning.
39. The gas law for an ideal gas at absolute temperature T (in
kelvins), pressure P (in atmospheres), and volume V (in
liters) is PV − nRT, where n is the number of moles of the
gas and R − 0.0821 is the gas constant. Suppose that, at a
certain instant, P − 8.0 atm and is increasing at a rate of
0.10 atmymin and V − 10 L and is decreasing at a rate of
0.15 Lymin. Find the rate of change of T with respect to
time at that instant if n − 10 mol.
40. In a fish farm, a population of fish is introduced into a pond
and harvested regularly. A model for the rate of change of
the fish population is given by the equation
S
D
Pstd
dP
Pstd 2 (Pstd
− r0 1 2
dt
Pc
where r0 is the birth rate of the fish, Pc is the maximum population that the pond can sustain (called the carrying capacity),
and ( is the percentage of the population that is harvested.
(a) What value of dPydt corresponds to a stable population?
(b) If the pond can sustain 10,000 fish, the birth rate is 5%,
and the harvesting rate is 4%, find the stable population
level.
(c) What happens if ( is raised to 5%?
41. In the study of ecosystems, predator-prey models are often
used to study the interaction between species. Consider
populations of tundra wolves, given by Wstd, and caribou,
given by Cstd, in northern Canada. The interaction has been
modeled by the equations
dC
− aC 2 bCW
dt
dW
− 2cW 1 dCW
dt
(a) What values of dCydt and dWydt correspond to stable
populations?
(b) How would the statement “The caribou go extinct” be
represented mathematically?
(c) Suppose that a − 0.05, b − 0.001, c − 0.05, and
d − 0.0001. Find all population pairs sC, W d that lead
to stable populations. According to this model, is it
possible for the two species to live in balance or will
one or both species become extinct?
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SECTION 3.8
42. Hermann Ebbinghaus (1850 –1909) pioneered the study of
memory. A 2011 article in the Journal of Mathematical Psychology presents the mathematical model
43. The difficulty of “acquiring a target” (such as using a mouse
to click on an icon on a computer screen) depends on the ratio
239
between the distance D to the target and width W of the target. According to Fitts’ law, the index I of difficulty is modeled by
S D
Rstd − a 1 bs1 1 ctd2(
for the Ebbinghaus forgetting curve, where Rstd is the fraction
of memory retained t days after learning a task; a, b, and c are
experimentally determined constants between 0 and 1; ( is a
positive constant; and Rs0d − 1. The constants depend on the
type of task being learned.
(a) What is the rate of change of retention t days after a task
is learned?
(b) Do you forget how to perform a task faster soon after
learning it or a long time after you have learned it?
(c) What fraction of memory is permanent?
Exponential Growth and Decay
I − log 2
2D
W
This law is used for designing products that involve human–
computer interactions.
(a) If W is held constant, what is the rate of change of I with
respect to D? Does this rate increase or decrease with
increasing values of D?
(b) If D is held constant, what is the rate of change of I
with respect to W? What does the negative sign in your
answer indicate? Does this rate increase or decrease
with increasing values of W?
(c) Do your answers to parts (a) and (b) agree with your
intuition?
3.8 Exponential Growth and Decay
In many natural phenomena, quantities grow or decay at a rate proportional to their size.
For instance, if y − f std is the number of individuals in a population of animals or bacteria at time t, then it seems reasonable to expect that the rate of growth f 9std is proportional to the population f std; that is, f 9std − kf std for some constant k. Indeed, under
ideal conditions (unlimited environment, adequate nutrition, immunity to disease) the
mathematical model given by the equation f 9std − kf std predicts what actually happens
fairly accurately. Another example occurs in nuclear physics: the mass of a radioactive
substance decays at a rate proportional to the mass. In chemistry, the rate of a unimolecular first-order reaction is proportional to the concentration of the substance. In
finance, the value of a savings account with continuously compounded interest increases
at a rate proportional to that value.
In general, if ystd is the value of a quantity y at time t and if the rate of change of y
with respect to t is proportional to its size ystd at any time, then
1
dy
− ky
dt
where k is a constant. Equation 1 is sometimes called the law of natural growth (if
k . 0d or the law of natural decay (if k , 0). It is called a differential equation because
it involves an unknown function y and its derivative dyydt.
It’s not hard to think of a solution of Equation 1. This equation asks us to find a
function whose derivative is a constant multiple of itself. We have met such functions in
this chapter. Any exponential function of the form ystd − Ce kt, where C is a constant,
satisfies
dy
− Cske kt d − ksCe kt d − ky
dt
We will see in Section 9.4 that any function that satisfies dyydt − ky must be of the form
y − Ce kt. To see the significance of the constant C, we observe that
ys0d − Ce k!0 − C
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240
CHAPTER 3
Differentiation Rules
Therefore C is the initial value of the function.
2 Theorem The only solutions of the differential equation dyydt − ky are the
exponential functions
ystd − ys0de kt
■ Population Growth
What is the significance of the proportionality constant k ? In the context of population
growth, where Pstd is the size of a population at time t, we can write
3
dP
− kP
dt
or
dPydt
−k
P
The quantity
dPydt
P
is the growth rate divided by the population size; it is called the relative growth rate.
According to (3), instead of saying “the growth rate is proportional to population size”
we could say “the relative growth rate is constant.” Then Theorem 2 says that a population with constant relative growth rate must grow exponentially. Notice that the relative
growth rate k appears as the coefficient of t in the exponential function Ce kt. For
instance, if
dP
− 0.02P
dt
and t is measured in years, then the relative growth rate is k − 0.02 and the population
grows at a relative rate of 2% per year. If the population at time 0 is P0 , then the expression for the population is
Pstd − P0 e 0.02t
EXAMPLE 1 Use the fact that the world population was 2560 million in 1950 and
3040 million in 1960 to model the population of the world in the second half of the
20th century. (Assume that the growth rate is proportional to the population size.) What
is the relative growth rate? Use the model to estimate the world population in 1993 and
to predict the population in the year 2025.
SOLUTION We measure the time t in years and let t − 0 in the year 1950. We measure
the population Pstd in millions of people. Then Ps0d − 2560 and Ps10d − 3040. Since
we are assuming that dPydt − kP, Theorem 2 gives
Pstd − Ps0de kt − 2560e kt
Ps10d − 2560e 10k − 3040
k−
1
3040
ln
< 0.017185
10
2560
The relative growth rate is about 1.7% per year and the model is
Pstd − 2560e 0.017185t
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SECTION 3.8
Exponential Growth and Decay
241
We estimate that the world population in 1993 was
Ps43d − 2560e 0.017185s43d < 5360 million
The model predicts that the population in 2025 will be
Ps75d − 2560e 0.017185s75d < 9289 million
The graph in Figure 1 shows that the model is fairly accurate to the end of the 20th century (the dots represent the actual population), so the estimate for 1993 is quite reliable.
But the prediction for 2025 may not be so accurate.
P
6000
P=2560e 0.017185t
Population
(in millions)
FIGURE 1
0
A model for world population growth
in the second half of the 20th century
20
40
t
Years since 1950
n
■ Radioactive Decay
Radioactive substances decay by spontaneously emitting radiation. If mstd is the mass
remaining from an initial mass m0 of the substance after time t, then the relative decay rate
2
dmydt
m
has been found experimentally to be constant. (Since dmydt is negative, the relative
decay rate is positive.) It follows that
dm
− km
dt
where k is a negative constant. In other words, radioactive substances decay at a rate
proportional to the remaining mass. This means that we can use Theorem 2 to show that
the mass decays exponentially:
mstd − m0 e kt
Physicists express the rate of decay in terms of half-life, the time required for half of
any given quantity to decay.
EXAMPLE 2 The half-life of radium-226 is 1590 years.
(a) A sample of radium-226 has mass 100 mg. Find a formula for the mass of the
sample that remains after t years.
(b) Find the mass remaining after 1000 years correct to the nearest milligram.
(c) When will the mass be reduced to 30 mg?
SOLUTION
(a) Let mstd be the mass of radium-226 (in milligrams) that remains after t years. Then
dmydt − km and ms0d − 100, so Theorem 2 gives
mstd − ms0de kt − 100e kt
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242
CHAPTER 3
Differentiation Rules
In order to determine the value of k, we use the fact that ms1590d − 12 s100d. Thus
100e 1590k − 50
e 1590k − 12
so
1590k − ln 12 − 2ln 2
and
k−2
ln 2
1590
mstd − 100e2sln 2dty1590
Therefore
We could use the fact that e ln 2 − 2 to write the expression for mstd in the alternative
form
mstd − 100 3 2 2ty1590
(b) The mass remaining after 1000 years is
ms1000d − 100e2sln 2d1000y1590 < 65 mg
(c) We want to find the value of t such that mstd − 30, that is,
100e2sln 2dty1590 − 30
or
e2sln 2dty1590 − 0.3
We solve this equation for t by taking the natural logarithm of both sides:
150
2
m=100e_(ln 2)t/1590
Thus
ln 2
t − ln 0.3
1590
t − 21590
m=30
4000
0
FIGURE 2
ln 0.3
< 2762 years
ln 2
n
As a check on our work in Example 2, we use a calculator or computer to draw the
graph of mstd in Figure 2 together with the horizontal line m − 30. These curves intersect
when t < 2800, and this agrees with the answer to part (c).
■ Newton’s Law of Cooling
Newton’s Law of Cooling states that the rate of cooling of an object is proportional to the
temperature difference between the object and its surroundings, provided that this difference is not too large. (This law also applies to warming.) If we let Tstd be the temperature of the object at time t and Ts be the temperature of the surroundings, then we can
formulate Newton’s Law of Cooling as a differential equation:
dT
− ksT 2 Ts d
dt
where k is a constant. This equation is not quite the same as Equation 1, so we make the
change of variable ystd − Tstd 2 Ts . Because Ts is constant, we have y9std − T 9std and
so the equation becomes
dy
− ky
dt
We can then use Theorem 2 to find an expression for y, from which we can find T.
EXAMPLE 3 A bottle of iced tea at room temperature (72°F) is placed in a refrigerator
where the temperature is 44°F. After half an hour the tea has cooled to 61°F.
(a) What is the temperature of the tea after another half hour?
(b) How long does it take for the tea to cool to 50°F ?
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SECTION 3.8
Exponential Growth and Decay
243
SOLUTION
(a) Let Tstd be the temperature of the tea after t minutes. The surrounding temperature
is Ts − 448 F, so Newton’s Law of Cooling states that
dT
− ksT 2 44d
dt
If we let y − T 2 44, then ys0d − Ts0d 2 44 − 72 2 44 − 28, so y satisfies
dy
− ky
dt
ys0d − 28
ystd − ys0de kt − 28e kt
and by (2) we have
We are given that Ts30d − 61, so ys30d − 61 2 44 − 17 and
e 30k − 17
28
28e 30k − 17
Taking logarithms, we have
k−
17
ln (28
) < 20.01663
30
Thus
ystd − 28e 20.01663t
Tstd − 44 1 28e 20.01663t
Ts60d − 44 1 28e 20.01663s60d < 54.3
So after another half hour the tea has cooled to about 54°F.
(b) We have Tstd − 50 when
44 1 28e 20.01663t − 50
6
e 20.01663t − 28
T (°F)
72
t−
6
ln (28
) < 92.6
20.01663
The tea cools to 50°F after about 1 hour 33 minutes.
44
n
Notice that in Example 3 we have
0
FIGURE 3
30
60
90
t
(min)
lim Tstd − lim s44 1 28e 20.01663t d − 44 1 28 ! 0 − 44
tl`
tl`
This means that, as expected, the temperature of the tea approaches the ambient temperature inside the refrigerator. The graph of the temperature function is shown in Figure 3.
■ Continuously Compounded Interest
EXAMPLE 4 If $5000 is invested at 2% interest, compounded annually, then after
1 year the investment is worth $5000s1.02d − $5100.00, after 2 years it’s worth
[$5000s1.02d]s1.02d − $5202.00, and after t years it’s worth $5000s1.02dt. In general,
if an amount A0 is invested at an interest rate r (r − 0.02 in this example), then after
t years it’s worth A0s1 1 rdt. Usually, interest is compounded more frequently, say,
n times per year. Then in each compounding period the rate is ryn, and there are
nt compounding periods in t years, so the value of the investment is
S D
A − A0 1 1
r
n
nt
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244
CHAPTER 3
Differentiation Rules
For instance, after 3 years at 2% interest a $5000 investment will be worth
$5000s1.02d3 − $5306.04 with annual compounding
$5000s1.01d6 − $5307.60 with semiannual compounding
$5000s1.005d12 − $5308.39 with quarterly compounding
S
$5000 1 1
0.02
12
S
D
$5000 1 1
0.02
365
D
36
− $5308.92 with monthly compounding
365?3
− $5309.17 with daily compounding
You can see that the interest paid increases as the number of compounding periods snd
increases. If we let n l `, then we will be compounding the interest continuously and
the value of the investment will be
S D
FS D G
F S DG
F S DG
Astd − lim A0 1 1
nl`
rt
11
r
n
nyr
− lim A0
rt
11
r
n
nyr
− A0 lim
rt
11
1
m
m
− A0 lim
nl`
nl`
ml `
Equation 3.6.6:
e − lim
nl`
S D
11
1
n
n
nt
r
n
(where m − nyr)
But the limit in this expression is equal to the number e (see Equation 3.6.6).
So with continuous compounding of interest at interest rate r, the amount after
t years is
Astd − A0 e rt
If we differentiate this equation, we get
dA
− rA0 e rt − rAstd
dt
which says that, with continuous compounding of interest, the rate of increase of an
investment is proportional to its size.
Returning to the example of $5000 invested for 3 years at 2% interest, we see that
with continuously compounding of interest the value of the investment will be
As3d − $5000es0.02d3 − $5309.18
Notice how close this is to the amount we calculated for daily compounding, $5309.17.
But the amount is easier to compute if we use continuous compounding.
n
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SECTION 3.8
Exponential Growth and Decay
245
3.8 Exercises
1. A population of the yeast cell Saccharomyces cerevisiae (a
yeast used for fermentation) develops with a constant relative
growth rate of 0.4159 per hour. The initial population
consists of 3.8 million cells. Find the population size after
2 hours.
2. A common inhabitant of human intestines is the bacterium
Escherichia coli, named after the German pediatrician
Theodor Escherich, who identified it in 1885. A cell of this
bacterium in a nutrient-broth medium divides into two cells
every 20 minutes. The initial population of a culture is
50 cells.
(a) Find the relative growth rate.
(b) Find an expression for the number of cells after t hours.
(c) Find the number of cells after 6 hours.
(d) Find the rate of growth after 6 hours.
(e) When will the population reach a million cells?
3. A culture of the bacterium Salmonella enteritidis initially
contains 50 cells. When introduced into a nutrient broth, the
culture grows at a rate proportional to its size. After 1.5 hours
the population has increased to 975.
(a) Find an expression for the number of bacteria after
t hours.
(b) Find the number of bacteria after 3 hours.
(c) Find the rate of growth after 3 hours.
(d) After how many hours will the population reach 250,000 ?
4. A bacteria culture grows with constant relative growth rate.
The bacteria count was 400 after 2 hours and 25,600 after
6 hours.
(a) What is the relative growth rate? Express your answer
as a percentage.
(b) What was the initial size of the culture?
(c) Find an expression for the number of bacteria after
t hours.
(d) Find the number of bacteria after 4.5 hours.
(e) Find the rate of growth after 4.5 hours.
(f ) When will the population reach 50,000 ?
5. The table gives estimates of the world population, in millions,
from 1750 to 2000.
(b) Use the exponential model and the population figures
for 1850 and 1900 to predict the world population in
1950. Compare with the actual population.
(c) Use the exponential model and the population figures for
1900 and 1950 to predict the world population in 2000.
Compare with the actual population and try to explain the
discrepancy.
6. The table gives census data for the population of Indonesia, in
millions, during the second half of the 20th century.
Year
Population
(millions)
1950
83
1960
100
1970
122
1980
150
1990
182
2000
214
(a) Assuming the population grows at a rate proportional
to its size, use the census data for 1950 and 1960 to
predict the population in 1980. Compare with the
actual figure.
(b) Use the census data for 1960 and 1980 to predict
the population in 2000. Compare with the actual
population.
(c) Use the census data for 1980 and 2000 to predict the
population in 2010 and compare with the actual population of 243 million.
(d) Use the model in part (c) to predict the population in
2025. Do you think the prediction will be too high or too
low? Why?
7. Experiments show that if the chemical reaction
N2O5 l 2NO 2 1 12 O 2
Year
Population
(millions)
Year
Population
(millions)
1750
1800
1850
790
980
1260
1900
1950
2000
1650
2560
6080
(a) Use the exponential model and the population figures for
1750 and 1800 to predict the world population in 1900
and 1950. Compare with the actual figures.
takes place at 45 8C, the rate of reaction of dinitrogen pentoxide is proportional to its concentration as follows:
2
dfN2O5g
− 0.0005fN2O5g
dt
(a) Find an expression for the concentration fN2O5g after
t seconds if the initial concentration is C.
(b) How long will the reaction take to reduce the concentration of N2O5 to 90% of its original value?
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246
CHAPTER 3
Differentiation Rules
8. Strontium-90 has a half-life of 28 days.
(a) A sample has initial mass 50 mg. Find a formula for the
mass remaining after t days.
(b) Find the mass remaining after 40 days.
(c) How long does it take the sample to decay to a mass
of 2 mg?
(d) Sketch the graph of the mass function.
9. The half-life of cesium-137 is 30 years. Suppose we have a
100-mg sample.
(a) Find the mass that remains after t years.
(b) How much of the sample remains after 100 years?
(c) After how long will only 1 mg remain?
10. A sample of einsteinium-252 decayed to 64.3% of its original
mass after 300 days.
(a) What is the half-life of einsteinium-252?
(b) How long would it take the sample to decay to one-third
of its original mass?
11–13 Radiocarbon Dating Scientists can determine the age
of ancient objects by the method of radiocarbon dating. The
bombardment of the upper atmosphere by cosmic rays converts
nitrogen to a radioactive isotope of carbon, 14 C, with a half-life of
about 5730 years. Vegetation absorbs carbon dioxide through the
atmosphere and animal life assimilates 14 C through food chains.
When a plant or animal dies, it stops replacing its carbon and the
amount of 14 C present begins to decrease through radioactive
decay. Therefore the level of radioactivity must also decay
exponentially.
11. A discovery revealed a parchment fragment that had about
74% as much 14 C radioactivity as does plant material on the
earth today. Estimate the age of the parchment.
12. Dinosaur fossils are too old to be reliably dated using
carbon-14. Suppose we had a 68-million-year-old dinosaur
fossil. What fraction of the living dinosaur’s 14 C would be
remaining today? Suppose the minimum detectable mass is
0.1%. What is the maximum age of a fossil that could be
dated using 14 C?
15. A roast turkey is removed from an oven when its temperature
has reached 185°F and is placed on a table in a room where
the ambient temperature is 75°F.
(a) If the temperature of the turkey is 150 8F after half an
hour, what is the temperature after 45 minutes?
(b) When will the turkey have cooled to 100 8F ?
16. In a murder investigation, the temperature of the corpse
was 32.5°C at 1:30 pm and 30.3°C an hour later. Normal
body temperature is 37.0°C and the ambient temperature
was 20.0°C. When did the murder take place?
17. When a cold drink is taken from a refrigerator, its temperature
is 5°C. After 25 minutes in a 20°C room its temperature has
increased to 10°C.
(a) What is the temperature of the drink after 50 minutes?
(b) When will its temperature reach 15°C?
18. A freshly brewed cup of coffee has temperature 958C in a
20°C room. When its temperature is 70°C, it is cooling at a
rate of 1°C per minute. When does this occur?
19. The rate of change of atmospheric pressure P with respect to
altitude h is proportional to P, provided that the temperature
is constant. At 15°C the pressure is 101.3 kPa at sea level and
87.14 kPa at h − 1000 m.
(a) What is the pressure at an altitude of 3000 m?
(b) What is the pressure at the top of Mount McKinley, at an
altitude of 6187 m?
20. (a) If $2500 is borrowed at 4.5% interest, find the amounts
due at the end of 3 years if the interest is compounded
(i) annually, (ii) quarterly, (iii) monthly, (iv) weekly,
(v) daily, (vi) hourly, and (vii) continuously.
(b) Suppose $2500 is borrowed and the interest is
;
compounded continuously. If Astd is the amount due
after t years, where 0 < t < 3, graph Astd for each of
the interest rates 5%, 6%, and 7% on a common
screen.
13. Dinosaur fossils are often dated by using an element other
than carbon, such as potassium-40, that has a longer half-life
(in this case, approximately 1.25 billion years). Suppose the
minimum detectable mass is 0.1% and a dinosaur is dated
with 40 K to be 68 million years old. Is such a dating possible?
In other words, what is the maximum age of a fossil that
could be dated using 40 K?
21. (a) If $4000 is invested at 1.75% interest, find the value of
the investment at the end of 5 years if the interest is compounded (i) annually, (ii) semiannually, (iii) monthly,
(iv) weekly, (v) daily, and (vi) continuously.
(b) If Astd is the amount of the investment at time t for
the case of continuous compounding, write a differential equation and an initial condition satisfied
by Astd.
14. A curve passes through the point s0, 5d and has the property
that the slope of the curve at every point P is twice the
y-coordinate of P. What is the equation of the curve?
22. (a) How long will it take an investment to double in value if
the interest rate is 3%, compounded continuously?
(b) What is the equivalent annual interest rate?
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SECTION 3.9
APPLIED PROJECT
Related Rates
247
CONTROLLING RED BLOOD CELL LOSS DURING SURGERY
A typical volume of blood in the human body is about 5 L . A certain percentage of that
volume (called the hematocrit) consists of red blood cells (RBCs); typically the hematocrit is
about 45% in males. Suppose that a surgery takes four hours and a male patient bleeds 2.5 L of
blood. During surgery the patient’s blood volume is maintained at 5 L by injection of saline
solution, which mixes quickly with the blood but dilutes it so that the hematocrit decreases as
time passes.
1. Assuming that the rate of RBC loss is proportional to the volume of RBCs, determine the
patient’s volume of RBCs by the end of the operation.
Ken Weakley
Kent
Weakley//Shutterstock.com
Shutterstock.com
2. A procedure called acute normovolemic hemodilution (ANH) has been developed to minimize RBC loss during surgery. In this procedure blood is extracted from the patient before
the operation and replaced with saline solution. This dilutes the patient’s blood, resulting
in fewer RBCs being lost by bleeding during surgery. The extracted blood is then returned
to the patient after surgery. Only a certain amount of blood can be extracted, however,
because the RBC concentration can never be allowed to drop below 25% during surgery.
What is the maximum amount of blood that can be extracted in the ANH procedure for the
surgery described in this project?
3. What is the RBC loss without the ANH procedure? What is the loss if the procedure is carried out with the volume calculated in Problem 2?
3.9 Related Rates
If we are pumping air into a balloon, both the volume and the radius of the balloon are
increasing and their rates of increase are related to each other. But it is much easier to
measure directly the rate of increase of the volume than the rate of increase of the radius.
In a related rates problem the idea is to compute the rate of change of one quantity in
terms of the rate of change of another quantity (which may be more easily measured).
The procedure is to find an equation that relates the two quantities and then use the Chain
Rule to differentiate both sides with respect to time.
EXAMPLE 1 Air is being pumped into a spherical balloon so that its volume increases
at a rate of 100 cm3ys. How fast is the radius of the balloon increasing when the diameter is 50 cm?
PS According to the Principles of Problem
Solving discussed following Chapter 1, the
first step is to understand the problem. This
includes reading the problem carefully,
identifying the given and the unknown, and
introducing suitable notation.
SOLUTION We start by identifying two things:
the given information:
the rate of increase of the volume of air is 100 cm3ys
and the unknown:
the rate of increase of the radius when the diameter is 50 cm
In order to express these quantities mathematically, we introduce some suggestive
notation:
Let V be the volume of the balloon and let r be its radius.
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248
CHAPTER 3
Differentiation Rules
The key thing to remember is that rates of change are derivatives. In this problem,
the volume and the radius are both functions of the time t. The rate of increase of the
volume with respect to time is the derivative dVydt, and the rate of increase of the
radius is drydt. We can therefore restate the given and the unknown as follows:
dV
− 100 cm3ys
dt
dr
when r − 25 cm
dt
Given:
Unknown:
In order to connect dVydt and drydt, we first relate V and r by a formula—in this
case, the formula for the volume of a sphere:
V − 43 !r 3
PS The second stage of problem solving is to
think of a plan for connecting the given and
the unknown.
In order to use the given information, we differentiate each side of this equation with
respect to t. To differentiate the right side, we need to use the Chain Rule:
dV
dV dr
dr
−
− 4!r 2
dt
dr dt
dt
Now we solve for the unknown quantity:
dr
1 dV
−
dt
4!r 2 dt
Notice that, although dVydt is constant, drydt is not constant.
If we put r − 25 and dVydt − 100 in this equation, we obtain
dr
1
1
−
100 −
dt
4!s25d2
25!
The radius of the balloon is increasing at the rate of 1ys25!d < 0.0127 cmys when the
diameter is 50 cm.
n
wall
EXAMPLE 2 A ladder 10 ft long rests against a vertical wall. If the bottom of the
ladder slides away from the wall at a rate of 4 ftys, how fast is the top of the ladder
sliding down the wall when the bottom of the ladder is 6 ft from the wall?
10
y
x
ground
FIGURE 1
SOLUTION We first draw a diagram and label it as in Figure 1. Let x feet be the distance
from the bottom of the ladder to the wall and y feet the distance from the top of the ladder
to the ground. Note that x and y are both functions of t (time, measured in seconds).
We are given that dxydt − 4 ftys and we are asked to find dyydt when x − 6 ft (see
Figure 2). In this problem, the relationship between x and y is given by the Pythagorean
Theorem:
x 2 1 y 2 − 100
Differentiating each side with respect to t using the Chain Rule, we have
2x
dy
=?
dt
Solving this equation for the desired rate, we obtain
y
dy
x dx
−2
dt
y dt
x
dx
=4
dt
FIGURE 2
dx
dy
1 2y
−0
dt
dt
When x − 6, the Pythagorean Theorem gives y − 8 and so, substituting these values
and dxydt − 4, we have
dy
6
− 2 s4d − 23 ftys
dt
8
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SECTION 3.9
Related Rates
249
The fact that dyydt is negative means that the distance from the top of the ladder to
the ground is decreasing at a rate of 3 ftys. In other words, the top of the ladder is
sliding down the wall at a rate of 3 ftys.
n
Problem Solving Strategy
It is useful to recall some of the problem-solving principles and adapt them to
related rates in light of our experience in Examples 1 and 2:
1. Read the problem carefully.
2. Draw a diagram if possible.
3. Introduce notation. Assign symbols to all quantities that are functions of time.
4. Express the given information and the required rate in terms of derivatives.
5. Write an equation that relates the various quantities of the problem. If necessary,
use the geometry of the situation to eliminate one of the variables by substitution (see Example 3 below).
6. Use the Chain Rule to differentiate both sides of the equation with respect to t.
7. Substitute the given information into the resulting equation and solve for the
unknown rate.
See also Principles of Problem Solving following Chapter 1.
PS Look back: What have we learned from
Examples 1 and 2 that will help us solve
future problems?
WARNING A common error is
to substitute the given numerical
information (for quantities that vary
with time) too early. This should be
done only after the differentiation.
(Step 7 follows Step 6.) For instance,
in Example 1 we dealt with general
values of r until we finally substituted
r − 25 at the last step. (If we had put
r − 25 earlier, we would have gotten
dVydt − 0, which is clearly wrong.)
The following examples further illustrate this strategy.
EXAMPLE 3 A water tank has the shape of an inverted circular cone with base radius
2 m and height 4 m. If water is being pumped into the tank at a rate of 2 m 3ymin, find
the rate at which the water level is rising when the water is 3 m deep.
2
r
4
h
SOLUTION We first sketch the cone and label it as in Figure 3. Let V, r, and h be the
volume of the water, the radius of the surface, and the height of the water at time t,
where t is measured in minutes.
We are given that dVydt − 2 m 3ymin and we are asked to find dhydt when h is 3 m.
The quantities V and h are related by the equation
V − 13 !r 2h
FIGURE 3
but it is very useful to express V as a function of h alone. In order to eliminate r, we use
the similar triangles in Figure 3 to write
r
2
−
h
4
and the expression for V becomes
V−
SD
1
h
!
3
2
r−
2
h−
h
2
! 3
h
12
Now we can differentiate each side with respect to t :
dV
! 2 dh
−
h
dt
4
dt
so
dh
4 dV
−
dt
!h 2 dt
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250
CHAPTER 3
Differentiation Rules
Substituting h − 3 m and dVydt − 2 m 3ymin, we have
dh
4
8
−
2 ! 2 −
dt
!s3d
9!
The water level is rising at a rate of 8ys9!d < 0.28 mymin.
n
EXAMPLE 4 Car A is traveling west at 50 miyh and car B is traveling north at
60 miyh. Both are headed for the intersection of the two roads. At what rate are
the cars approaching each other when car A is 0.3 mi and car B is 0.4 mi from the
intersection?
x
C
y
z
B
A
SOLUTION We draw Figure 4, where C is the intersection of the roads. At a given
time t, let x be the distance from car A to C, let y be the distance from car B to C,
and let z be the distance between the cars, where x, y, and z are measured in miles.
We are given that dxydt − 250 miyh and dyydt − 260 miyh. (The derivatives are
negative because x and y are decreasing.) We are asked to find dzydt. The equation that
relates x, y, and z is given by the Pythagorean Theorem:
z2 − x 2 1 y 2
FIGURE 4
Differentiating each side with respect to t, we have
2z
dz
dx
dy
− 2x
1 2y
dt
dt
dt
dz
1
−
dt
z
S
x
dx
dy
1y
dt
dt
D
When x − 0.3 mi and y − 0.4 mi, the Pythagorean Theorem gives z − 0.5 mi, so
dz
1
−
f0.3s250d 1 0.4s260dg − 278 miyh
dt
0.5
The cars are approaching each other at a rate of 78 miyh.
n
EXAMPLE 5 A man walks along a straight path at a speed of 4 ftys. A spotlight is located
on the ground 20 ft from the path and is kept focused on the man. At what rate is the
spotlight rotating when the man is 15 ft from the point on the path closest to the light?
SOLUTION We draw Figure 5 and let x be the distance from the man to the point on the
path closest to the spotlight. We let " be the angle between the beam of the light and the
perpendicular to the path.
We are given that dxydt − 4 ftys and are asked to find d"ydt when x − 15. The
equation that relates x and " can be written from Figure 5:
x
20
¨
x
− tan "
20
x − 20 tan "
Differentiating each side with respect to t, we get
dx
d"
− 20 sec2"
dt
dt
FIGURE 5
so
d"
1
dx
−
cos2"
dt
20
dt
−
1
1
cos2" s4d − cos2"
20
5
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SECTION 3.9
Related Rates
251
4
When x − 15, the length of the beam is 25, so cos " − 20
25 − 5 and
d"
1
−
dt
5
rad
1 rotation
60 s
0.128
3
3
s
2! rad
1 min
< 1.22 rotations per min
SD
4
5
2
−
16
− 0.128
125
The spotlight is rotating at a rate of 0.128 radys.
n
3.9 Exercises
1. (a) If V is the volume of a cube with edge length x and the
cube expands as time passes, find dVydt in terms of
dxydt.
(b) If the length of the edge of a cube is increasing at a rate
of 4 cmys, how fast is the volume of the cube increasing
when the edge length is 15 cm?
2. (a) If A is the area of a circle with radius r and the circle
expands as time passes, find dAydt in terms of drydt.
(b) Suppose oil spills from a ruptured tanker and spreads in a
circular pattern. If the radius of the oil spill increases at a
constant rate of 2 mys, how fast is the area of the spill
increasing when the radius is 30 m?
3. Each side of a square is increasing at a rate of 6 cmys. At
what rate is the area of the square increasing when the area of
the square is 16 cm2 ?
4. The radius of a sphere is increasing at a rate of 4 mmys. How
fast is the volume increasing when the diameter is 80 mm?
5. The radius of a spherical ball is increasing at a rate of
2 cmymin. At what rate is the surface area of the ball increasing when the radius is 8 cm?
6. The length of a rectangle is increasing at a rate of 8 cmys and
its width is increasing at a rate of 3 cmys. When the length is
20 cm and the width is 10 cm, how fast is the area of the rectangle increasing?
7. A cylindrical tank with radius 5 m is being filled with water
at a rate of 3 m3ymin. How fast is the height of the water
increasing?
8. The area of a triangle with sides of lengths a and b and
contained angle " is A − 12 ab sin ". (See Formula 6 in
Appendix D.)
(a) If a − 2 cm, b − 3 cm, and " increases at a rate of
0.2 radymin, how fast is the area increasing when
" − !y3?
(b) If a − 2 cm, b increases at a rate of 1.5 cmymin, and "
increases at a rate of 0.2 radymin, how fast is the area
increasing when b − 3 cm and " − !y3?
(c) If a increases at a rate of 2.5 cmymin, b increases at a
rate of 1.5 cmymin, and " increases at a rate of
0.2 radymin, how fast is the area increasing when
a − 2 cm, b − 3 cm, and " − !y3?
9. Suppose 4x 2 1 9y 2 − 25, where x and y are functions of t.
(a) If dyydt − 13, find dxydt when x − 2 and y − 1.
(b) If dxydt − 3, find dy ydt when x − 22 and y − 1.
10. If x 2 1 y 2 1 z 2 − 9, dxydt − 5, and dyydt − 4, find dzydt
when sx, y, zd − s2, 2, 1d.
11. The weight w of an astronaut (in pounds) is related to her
height h above the surface of the earth (in miles) by
S
w − w0
3960
3960 1 h
D
2
where w0 is the weight of the astronaut on the surface of the
earth. If the astronaut weighs 130 pounds on earth and is in
a rocket, being propelled upward at a speed of 12 miys, find
the rate at which her weight is changing (in lbys) when she is
40 miles above the earth’s surface.
12. A particle is moving along a hyperbola xy − 8. As it reaches
the point s4, 2d, the y-coordinate is decreasing at a rate of
3 cmys. How fast is the x-coordinate of the point changing at
that instant?
13–16
(a) What quantities are given in the problem?
(b) What is the unknown?
(c) Draw a picture of the situation for any time t.
(d) Write an equation that relates the quantities.
(e) Finish solving the problem.
13. A plane flying horizontally at an altitude of 1 mi and a speed
of 500 miyh passes directly over a radar station. Find the rate
at which the distance from the plane to the station is increasing when the plane is 2 mi away from the station.
14. If a snowball melts so that its surface area decreases at a rate
of 1 cm2ymin, find the rate at which the diameter decreases
when the diameter is 10 cm.
15. A street light is mounted at the top of a 15-ft-tall pole. A man
6 ft tall walks away from the pole with a speed of 5 ftys along
a straight path. How fast is the tip of his shadow moving
when he is 40 ft from the pole?
16. At noon, ship A is 150 km west of ship B. Ship A is sailing
east at 35 kmyh and ship B is sailing north at 25 kmyh. How
fast is the distance between the ships changing at 4:00 pm?
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252
CHAPTER 3
Differentiation Rules
17. Two cars start moving from the same point. One travels south
at 60 miyh and the other travels west at 25 miyh. At what rate
is the distance between the cars increasing two hours later?
18. A spotlight on the ground shines on a wall 12 m away. If a
man 2 m tall walks from the spotlight toward the building at a
speed of 1.6 mys, how fast is the length of his shadow on the
building decreasing when he is 4 m from the building?
19. A man starts walking north at 4 ftys from a point P. Five
minutes later a woman starts walking south at 5 ftys from a
point 500 ft due east of P. At what rate are the people moving
apart 15 min after the woman starts walking?
20. A baseball diamond is a square with side 90 ft. A batter hits
the ball and runs toward first base with a speed of 24 ftys.
(a) At what rate is his distance from second base decreasing
when he is halfway to first base?
(b) At what rate is his distance from third base increasing at
the same moment?
90 ft
25. Water is leaking out of an inverted conical tank at a rate of
10,000 cm 3ymin at the same time that water is being pumped
into the tank at a constant rate. The tank has height 6 m and
the diameter at the top is 4 m. If the water level is rising at a
rate of 20 cmymin when the height of the water is 2 m, find
the rate at which water is being pumped into the tank.
26. A particle moves along the curve y − 2 sins!xy2d. As the
particle passes through the point ( 13 , 1), its x-coordinate
increases at a rate of s10 cmys. How fast is the distance
from the particle to the origin changing at this instant?
27. A water trough is 10 m long and a cross-section has the shape
of an isosceles trapezoid that is 30 cm wide at the bottom,
80 cm wide at the top, and has height 50 cm. If the trough is
being filled with water at the rate of 0.2 m 3ymin, how fast is
the water level rising when the water is 30 cm deep?
28. A trough is 10 ft long and its ends have the shape of isosceles triangles that are 3 ft across at the top and have a height
of 1 ft. If the trough is being filled with water at a rate of
12 ft 3ymin, how fast is the water level rising when the water
is 6 inches deep?
29. Gravel is being dumped from a conveyor belt at a rate of
30 ft 3ymin, and its coarseness is such that it forms a pile in
the shape of a cone whose base diameter and height are
always equal. How fast is the height of the pile increasing
when the pile is 10 ft high?
21. The altitude of a triangle is increasing at a rate of 1 cmymin
while the area of the triangle is increasing at a rate of
2 cm 2ymin. At what rate is the base of the triangle changing
when the altitude is 10 cm and the area is 100 cm2 ?
22. A boat is pulled into a dock by a rope attached to the bow of
the boat and passing through a pulley on the dock that is 1 m
higher than the bow of the boat. If the rope is pulled in at a
rate of 1 mys, how fast is the boat approaching the dock when
it is 8 m from the dock?
23–24 Use the fact that the distance (in meters) a dropped stone
falls after t seconds is d − 4.9t 2.
30. A swimming pool is 20 ft wide, 40 ft long, 3 ft deep at the
shallow end, and 9 ft deep at its deepest point. A cross-section
is shown in the Large
figure.size
If the
pool is being filled at a rate of
is preferable:
0.8 ft 3ymin, how fast is the water level rising when the depth
at the deepest point is 5 ft?
23. A woman stands near the edge of a cliff and drops a stone
over the edge. Exactly one second later she drops another
stone. One second after that, how fast is the distance between
the two stones changing?
24. Two men stand 10 m apart on level ground near the edge of a
cliff. One man drops a stone and one second later the other
man drops a stone. One second after that, how fast is the distance between the two stones changing?
3
6
6
12
16
6
31. The sides of an equilateral triangle are increasing at a rate of
10 cmymin. At what rate is the area of the triangle increasing
when the sides are 30 cm long?
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3
SECTION 3.9
32. A kite 100 ft above the ground moves horizontally at a speed
of 8 ftys. At what rate is the angle between the string and the
horizontal decreasing when 200 ft of string has been let out?
33. A car is traveling north on a straight road at 20 mys and a
drone is flying east at 6 mys at an elevation of 25 m. At one
instant the drone passes directly over the car. How fast is the
distance between the drone and the car changing 5 seconds
later?
34. If the minute hand of a clock has length r (in centimeters),
find the rate at which it sweeps out area as a function of r.
35. How fast is the angle between the ladder and the ground
changing in Example 2 when the bottom of the ladder is 6 ft
from the wall?
36. According to the model we used to solve Example 2, what
happens as the top of the ladder approaches the ground? Is
the model appropriate for small values of y?
37. Boyle’s Law states that when a sample of gas is compressed
at a constant temperature, the pressure P and volume V satisfy the equation PV − C , where C is a constant. Suppose
that at a certain instant the volume is 600 cm3, the pressure
is 150 kPa, and the pressure is increasing at a rate of
20 kPaymin. At what rate is the volume decreasing at this
instant?
; 38. A faucet is filling a hemispherical basin of diameter 60 cm
with water at a rate of 2 Lymin. Find the rate at which the
water is rising in the basin when it is half full. [Use the following facts: 1 L is 1000 cm3. The volume of the portion
of a sphere with radius r from the bottom to a height h is
V − ! (rh 2 2 13 h 3), as we will show in Chapter 6.]
39. If two resistors with resistances R1 and R2 are connected in
parallel, as shown in the figure, then the total resistance R,
measured in ohms (V), is given by
1
1
1
−
1
R
R1
R2
If R1 and R2 are increasing at rates of 0.3 Vys and 0.2 Vys,
respectively, how fast is R changing when R1 − 80 V
and R2 − 100 V?
R¡
R™
40. When air expands adiabatically (without gaining or losing
heat), its pressure P and volume V are related by the equation PV 1.4 − C , where C is a constant. Suppose that at a
certain instant the volume is 400 cm3 and the pressure is
80 kPa and is decreasing at a rate of 10 kPaymin. At what
rate is the volume increasing at this instant?
Related Rates
253
41. Two straight roads diverge from an intersection at an angle
of 60°. Two cars leave the intersection at the same time, the
first traveling down one road at 40 miyh and the second traveling down the other road at 60 miyh. How fast is the distance between the cars changing after half an hour? [Hint:
Use the Law of Cosines (Formula 21 in Appendix D).]
42. Brain weight B as a function of body weight W in fish has
been modeled by the power function B − 0.007W 2y3, where
B and W are measured in grams. A model for body weight
as a function of body length L (measured in centimeters) is
W − 0.12L2.53. If, over 10 million years, the average length
of a certain species of fish evolved from 15 cm to 20 cm at a
constant rate, how fast was this species’ brain growing
when its average length was 18 cm?
43. Two sides of a triangle have lengths 12 m and 15 m. The
angle between them is increasing at a rate of 2 8ymin. How
fast is the length of the third side increasing when the angle
between the sides of fixed length is 60°? [Hint: Use the Law
of Cosines (Formula 21 in Appendix D).]
44. Two carts, A and B, are connected by a rope 39 ft long that
passes over a pulley P. (See the figure.) The point Q is on the
floor 12 ft directly beneath P and between the carts. Cart A is
being pulled away from Q at a speed of 2 ftys. How fast is
cart B moving toward Q at the instant when cart A is 5 ft
from Q?
P
12 ft
A
B
Q
45. A television camera is positioned 4000 ft from the base of a
rocket launching pad. The angle of elevation of the camera
has to change at the correct rate in order to keep the rocket
in sight. Also, the mechanism for focusing the camera has to
take into account the increasing distance from the camera to
the rising rocket. Let’s assume the rocket rises vertically and
its speed is 600 ftys when it has risen 3000 ft.
(a) How fast is the distance from the television camera to
the rocket changing at that moment?
(b) If the television camera is always kept aimed at the
rocket, how fast is the camera’s angle of elevation
changing at that same moment?
46. A lighthouse is located on a small island 3 km away from
the nearest point P on a straight shoreline and its light
makes four revolutions per minute. How fast is the beam of
light moving along the shoreline when it is 1 km from P ?
47. A plane flies horizontally at an altitude of 5 km and passes
directly over a tracking telescope on the ground. When the
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254
CHAPTER 3
Differentiation Rules
angle of elevation is !y3, this angle is decreasing at a rate of
!y6 radymin. How fast is the plane traveling at that time?
48. A Ferris wheel with a radius of 10 m is rotating at a rate of
one revolution every 2 minutes. How fast is a rider rising
when his seat is 16 m above ground level?
49. A plane flying with a constant speed of 300 kmyh passes over
a ground radar station at an altitude of 1 km and climbs at an
angle of 308. At what rate is the distance from the plane to the
radar station increasing a minute later?
50. Two people start from the same point. One walks east at
3 miyh and the other walks northeast at 2 miyh. How fast is
the distance between the people changing after 15 minutes?
3.10
51. A runner sprints around a circular track of radius 100 m at
a constant speed of 7 mys. The runner’s friend is standing
at a distance 200 m from the center of the track. How fast is
the distance between the friends changing when the distance
between them is 200 m?
52. The minute hand on a watch is 8 mm long and the hour hand
is 4 mm long. How fast is the distance between the tips of the
hands changing at one o’clock?
53. Suppose that the volume V of a rolling snowball increases so
that dVydt is proportional to the surface area of the snowball
at time t. Show that the radius r increases at a constant rate,
that is, drydt is constant.
Linear Approximations and Differentials
We have seen that a curve lies very close to its tangent line near the point of tangency. In
fact, by zooming in toward a point on the graph of a differentiable function, we noticed
that the graph looks more and more like its tangent line. (See Figure 2.7.2.) This observation is the basis for a method of finding approximate values of functions.
■ Linearization and Approximation
y
It might be easy to calculate a value f sad of a function, but difficult (or even impossible)
to compute nearby values of f . So we settle for the easily computed values of the linear
function L whose graph is the tangent line of f at sa, f sadd. (See Figure 1.)
In other words, we use the tangent line at sa, f sadd as an approximation to the curve
y − f sxd when x is near a. An equation of this tangent line is
y=ƒ
{a, f(a)}
y=L(x)
y − f sad 1 f 9sadsx 2 ad
The linear function whose graph is this tangent line, that is,
0
x
FIGURE 1
1
Lsxd − f sad 1 f 9sadsx 2 ad
is called the linearization of f at a. The approximation f sxd < Lsxd or
2
f sxd < f sad 1 f 9sadsx 2 ad
is called the linear approximation or tangent line approximation of f at a.
EXAMPLE 1 Find the linearization of the function f sxd − sx 1 3 at a − 1 and use
it to approximate the numbers s3.98 and s4.05 . Are these approximations overestimates or underestimates?
SOLUTION The derivative of f sxd − sx 1 3d1y2 is
f 9sxd − 12 sx 1 3d21y2 −
1
2sx 1 3
and so we have f s1d − 2 and f 9s1d − 14. Putting these values into Equation 1, we see
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SECTION 3.10
Linear Approximations and Differentials
255
that the linearization is
Lsxd − f s1d 1 f 9s1dsx 2 1d − 2 1 14 sx 2 1d −
7
x
1
4
4
The corresponding linear approximation (2) is
sx 1 3 <
7
x
1
4
4
(when x is near 1)
In particular, we have
y
7
s3.98 < 74 1 0.98
4 − 1.995
x
y= 4 + 4
_3
FIGURE 2
(1, 2)
0
1
y= œ„„„„
x+3
x
s4.05 < 74 1 1.05
4 − 2.0125
and
The linear approximation is illustrated in Figure 2. We see that, indeed, the tangent line
approximation is a good approximation to the given function when x is near l. We also
see that our approximations are overestimates because the tangent line lies above the
curve.
Of course, a calculator could give us approximations for s3.98 and s4.05 , but the
linear approximation gives an approximation over an entire interval.
n
In the following table we compare the estimates from the linear approximation in
Example 1 with the true values. Notice from this table, and also from Figure 2, that the
tangent line approximation gives good estimates when x is close to 1 but the accuracy of
the approximation deteriorates when x is farther away from 1.
s3.9
s3.98
s4
s4.05
s4.1
s5
s6
x
From Lsxd
Actual value
0.9
0.98
1
1.05
1.1
2
3
1.975
1.995
2
2.0125
2.025
2.25
2.5
1.97484176. . .
1.99499373. . .
2.00000000. . .
2.01246117. . .
2.02484567. . .
2.23606797. . .
2.44948974. . .
How good is the approximation that we obtained in Example 1? The next example
shows that by using a graphing calculator or computer we can determine an interval
throughout which a linear approximation provides a specified accuracy.
EXAMPLE 2 For what values of x is the linear approximation
sx 1 3 <
7
x
1
4
4
accurate to within 0.5? What about accuracy to within 0.1?
SOLUTION Accuracy to within 0.5 means that the functions should differ by less
than 0.5:
7
x
1
, 0.5
sx 1 3 2
4
4
Z
S DZ
Equivalently, we could write
sx 1 3 2 0.5 ,
7
x
1 , sx 1 3 1 0.5
4
4
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256
CHAPTER 3
Differentiation Rules
This says that the linear approximation should lie between the curves obtained by shifting the curve y − sx 1 3 upward and downward by an amount 0.5. Figure 3 shows
the tangent line y − s7 1 xdy4 intersecting the upper curve y − sx 1 3 1 0.5 at P
and Q. We estimate that the x-coordinate of P is about 22.66 and the x-coordinate of Q
is about 8.66. Thus we see from the graph that the approximation
4.3
Q
y= œ„„„„
x+3+0.5
L (x)
P
y= œ„„„„
x+3-0.5
_4
10
sx 1 3 <
_1
FIGURE 3
3
is accurate to within 0.5 when 22.6 , x , 8.6. (We have rounded the smaller value up
and the larger value down.)
Similarly, from Figure 4 we see that the approximation is accurate to within 0.1
when 21.1 , x , 3.9.
n
Q
y= œ„„„„
x+3+0.1
■ Applications to Physics
y= œ„„„„
x+3-0.1
P
_2
1
7
x
1
4
4
5
FIGURE 4
Linear approximations are often used in physics. In analyzing the consequences of an
equation, a physicist sometimes needs to simplify a function by replacing it with its linear approximation. For instance, in deriving a formula for the period of a pendulum,
physics textbooks obtain an expression involving sin " and then replace sin " by " with
the remark that sin " is very close to " if " is not too large. You can verify that the linearization of the function f sxd − sin x at a − 0 is Lsxd − x and so the linear approximation
at 0 is
sin x < x
(see Exercise 50). So, in effect, the derivation of the formula for the period of a pendulum
uses the tangent line approximation for the sine function.
Another example occurs in the theory of optics, where light rays that arrive at shallow
angles relative to the optical axis are called paraxial rays. In paraxial (or Gaussian)
optics, both sin " and cos " are replaced by their linearizations. In other words, the linear
approximations
sin " < "
and
cos " < 1
are used because " is close to 0. The results of calculations made with these approximations became the basic theoretical tool used to design lenses. (See Optics, 5th ed., by
Eugene Hecht [Boston, 2017], p. 164.)
In Section 11.11 we will present several other applications of the idea of linear approximations to physics and engineering.
■ Differentials
If dx ± 0, we can divide both sides of
Equation 3 by dx to obtain
dy
− f 9sxd
dx
We have seen similar equations
before, but now the left side can genuinely be interpreted as a ratio of
differentials.
The ideas behind linear approximations are sometimes formulated in the terminology
and notation of differentials. If y − f sxd, where f is a differentiable function, then the
differential dx is an independent variable; that is, dx can be given the value of any real
number. The differential dy is then defined in terms of dx by the equation
3
dy − f 9sxd dx
So dy is a dependent variable; it depends on the values of x and dx. If dx is given a specific value and x is taken to be some specific number in the domain of f , then the numerical value of dy is determined.
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SECTION 3.10
Linear Approximations and Differentials
257
The geometric meaning of differentials is shown in Figure 5. Let Psx, f sxdd and
Qsx 1 Dx, f sx 1 Dxdd be points on the graph of f and let dx − Dx. The corresponding
change in y is
Dy − f sx 1 Dxd 2 f sxd
The slope of the tangent line PR is the derivative f 9sxd. Thus the directed distance from
S to R is f 9sxd dx − dy. Therefore dy represents the amount that the tangent line rises or
falls (the change in the linearization), whereas Dy represents the amount that the curve
y − f sxd rises or falls when x changes
by an amount dx.
Prefer larger art, set in text:
y
R
Q
dy
Îy
S
P
dx=Î x
0
x
x
x+Î x
y=ƒ
FIGURE 5
EXAMPLE 3 Compare the values of Dy and dy if y − f sxd − x 3 1 x 2 2 2x 1 1 and
x changes (a) from 2 to 2.05 and (b) from 2 to 2.01.
SOLUTION
(a) We have
f s2d − 2 3 1 2 2 2 2s2d 1 1 − 9
f s2.05d − s2.05d3 1 s2.05d2 2 2s2.05d 1 1 − 9.717625
Dy − f s2.05d 2 f s2d − 0.717625
Figure 6 shows the function in
Example 3 and a comparison of dy
and Dy when a − 2. The viewing
rectangle is f1.8, 2.5g by f6, 18g.
y=˛+≈-2x+1
dy
(2, 9)
FIGURE 6
When x − 2 and dx − Dx − 0.05, this becomes
Îy
dy
dy − f3s2d2 1P2s2d 2 2g0.05 − 0.7
(b)
Îy
y
dy − f 9sxd dx − s3xQ2 1R2x 2 2d dx
In general,
dx=Î
x
2
S
f s2.01d − s2.01d 1 s2.01d 2 2s2.01d 1 1 − 9.140701
3
0
x
x+Îx
Dy − f s2.01d 2 f s2d − 0.140701
When dx − Dx − 0.01,
x
y=ƒ
dy − f3s2d2 1 2s2d 2 2g0.01 − 0.14
n
Notice that the approximation Dy < dy becomes better as Dx becomes smaller in
Example 3. Notice also that dy was easier to compute than Dy.
In the notation of differentials, the linear approximation f sxd < f sad 1 f 9sadsx 2 ad
can be written as
f sa 1 dxd < f sad 1 dy
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258
CHAPTER 3
Differentiation Rules
by taking dx − x 2 a, so x − a 1 dx. For instance, for the function f sxd − sx 1 3 in
Example 1, we have
dy − f 9sxd dx −
dx
2 sx 1 3
If a − 1 and dx − Dx − 0.05, then
dy −
and
0.05
2 s1 1 3
− 0.0125
s4.05 − f s1.05d − f s1 1 0.05d < f s1d 1 dy − 2.0125
just as we found in Example 1.
Our final example illustrates the use of differentials in estimating the errors that occur
because of approximate measurements.
EXAMPLE 4 The radius of a sphere was measured and found to be 21 cm with a
possible error in measurement of at most 0.05 cm. What is the maximum error in using
this value of the radius to compute the volume of the sphere?
SOLUTION If the radius of the sphere is r, then its volume is V − 43 !r 3. If the error in
the measured value of r is denoted by dr − Dr, then the corresponding error in the
calculated value of V is DV, which can be approximated by the differential
dV − 4!r 2 dr
When r − 21 and dr − 0.05, this becomes
dV − 4!s21d2 0.05 < 277
The maximum error in the calculated volume is about 277 cm3.
n
NOTE Although the possible error in Example 4 may appear to be rather large, a better
picture of the error is given by the relative error, which is computed by dividing the
error by the total volume:
DV
dV
4!r 2 dr
dr
<
− 4 3 −3
V
V
r
3 !r
Thus the relative error in the volume is about three times the relative error in the radius.
In Example 4 the relative error in the radius is approximately dryr − 0.05y21 < 0.0024
and it produces a relative error of about 0.007 in the volume. The errors could also be
expressed as percentage errors of 0.24% in the radius and 0.7% in the volume.
3.10
Exercises
1–4 Find the linearization Lsxd of the function at a.
1. f sxd − x 2 x 1 3, a − 22
3
2. f sxd − e 3x,
2
a−0
3
x, a − 8
3. f sxd − s
4. f sxd − cos 2x,
a − !y6
; 5. Find the linear approximation of the function
f sxd − s1 2 x at a − 0 and use it to approximate the
numbers s0.9 and s0.99 . Illustrate by graphing f and the
tangent line.
; 6. Find the linear approximation of the function
3
tsxd − s
1 1 x at a − 0 and use it to approximate the
3
3
numbers s
0.95 and s
1.1 . Illustrate by graphing t and the
tangent line.
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SECTION 3.10
; 7–10 Verify the given linear approximation at a − 0. Then
determine the values of x for which the linear approximation is
accurate to within 0.1.
7. tan21x < x
9.
39.
1 1 2u
13. y −
1 1 3u
14. y − " sin 2"
1
15. y − 2
x 2 3x
16. y − s1 1 cos "
17. y − lnssin "d
18. y −
2
ex
1 2 ex
19–22 (a) Find the differential dy and (b) evaluate dy for the
given values of x and dx.
x − 0,
x − 13,
20. y − cos ! x,
21. y − s3 1 x ,
x11
,
x21
dx − 0.1
dx − 20.02
x − 1, dx − 20.1
2
22. y −
x − 2, dx − 0.05
23–26 Compute Dy and dy for the given values of x and
dx − Dx. Then sketch a diagram like Figure 5 showing the line
segments with lengths dx, dy, and Dy.
23. y − x 2 2 4x,
x − 3, Dx − 0.5
24. y − x 2 x 3,
x − 0, Dx − 20.3
25. y − sx 2 2 ,
x − 3, Dx − 0.8
x
26. y − e ,
and
12. y − s1 2 t 4
19. y − e x y10,
;
f sxd − sx 2 1d 2
tsxd − e22x
hsxd − 1 1 lns1 2 2xd
(a) Find the linearizations of f , t, and h at a − 0. What do
you notice? How do you explain what happened?
(b) Graph f , t, and h and their linear approximations. For
which function is the linear approximation best? For
which is it worst? Explain.
41. The edge of a cube was found to be 30 cm with a possible
error in measurement of 0.1 cm. Use differentials to estimate the maximum possible error, relative error, and percentage error in computing (a) the volume of the cube and
(b) the surface area of the cube.
42. The radius of a circular disk is given as 24 cm with a maximum error in measurement of 0.2 cm.
(a) Use differentials to estimate the maximum error in the
calculated area of the disk.
(b) What is the relative error and the percentage error?
43. The circumference of a sphere was measured to be 84 cm
with a possible error of 0.5 cm.
(a) Use differentials to estimate the maximum error in the
calculated surface area. What is the relative error?
(b) Use differentials to estimate the maximum error in the
calculated volume. What is the relative error?
44. Use differentials to estimate the amount of paint needed to
apply a coat of paint 0.05 cm thick to a hemispherical dome
with diameter 50 m.
x − 0, Dx − 0.5
27–30 Compare the values of Dy and dy if x changes from 1 to
1.05. What if x changes from 1 to 1.01? Does the approximation
Dy < dy become better as D x gets smaller?
27. f sxd − x 2 x 1 1
28. f sxd − e
29. f sxd − s5 2 x
30. f sxd −
4
1
< 0.1002
9.98
40. Let
11–18 Find the differential of the function.
11. y − e 5x
38. s4.02 < 2.005
37. ln 1.04 < 0.04
2
10.
< 1 2 12 x
1 1 ex
s1 1 2x < 1 1 12 x
259
37–39 Explain, in terms of linear approximations or differentials, why the approximation is reasonable.
8. s1 1 xd23 < 1 2 3x
4
Linear Approximations and Differentials
2x22
1
x2 1 1
31–36 Use a linear approximation (or differentials) to estimate
the given number.
31. s1.999d4
32. 1y4.002
3
33. s
1001
34. s100.5
35. e 0.1
36. cos 29°
45. (a) Use differentials to find a formula for the approximate
volume of a thin cylindrical shell with height h, inner
radius r, and thickness Dr.
(b) What is the error involved in using the formula from
part (a)?
46. One side of a right triangle is known to be 20 cm long and
the opposite angle is measured as 30°, with a possible error
of 61°.
(a) Use differentials to estimate the error in computing the
length of the hypotenuse.
(b) What is the percentage error?
47. If a current I passes through a resistor with resistance R,
Ohm’s Law states that the voltage drop is V − RI. If V is
constant and R is measured with a certain error, use differentials to show that the relative error in calculating I is
approximately the same (in magnitude) as the relative
error in R.
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260
CHAPTER 3
Differentiation Rules
48. When blood flows along a blood vessel, the flux F (the volume of blood per unit time that flows past a given point) is
proportional to the fourth power of the radius R of the blood
vessel:
F − kR 4
(This is known as Poiseuille’s Law; we will show why it
is true in Section 8.4.) A partially clogged artery can be
expanded by an operation called angioplasty, in which a
balloon-tipped catheter is inflated inside the artery in order
to widen it and restore normal blood flow.
Show that the relative change in F is about four times the
relative change in R. How will a 5% increase in the radius
affect the flow of blood?
49. Establish the following rules for working with differentials
(where c denotes a constant and u and v are functions of x).
(a) dc − 0
(b) dscud − c du
(c) dsu 1 vd − du 1 dv
(d) dsuvd − u dv 1 v du
SD
(e) d
u
v
−
v du 2 u dv
v2
(f ) dsx n d − nx n21 dx
50. In physics textbooks, the period T of a pendulum of length L
is often given as T < 2! sLyt , provided that the pendulum
swings through a relatively small arc. In the course of deriving this formula, the equation a T − 2t sin " for the tangential
acceleration of the bob of the pendulum is obtained, and then
sin " is replaced by " with the remark that for small angles, "
(in radians) is very close to sin ".
DISCOVERY PROJECT
(a) Verify the linear approximation at 0 for the sine function:
sin " < "
;
(b) If " − !y18 (equivalent to 10°) and we approximate
sin " by ", what is the percentage error?
(c) Use a graph to determine the values of " for which sin "
and " differ by less than 2%. What are the values in
degrees?
51. Suppose that the only information we have about a function f
is that f s1d − 5 and the graph of its derivative is as shown.
(a) Use a linear approximation to estimate f s0.9d and f s1.1d.
(b) Are your estimates in part (a) too large or too small?
Explain.
y
y=fª(x)
1
0
1
x
52. Suppose that we don’t have a formula for tsxd but we know
that ts2d − 24 and t9sxd − sx 2 1 5 for all x.
(a) Use a linear approximation to estimate ts1.95d and ts2.05d.
(b) Are your estimates in part (a) too large or too small?
Explain.
; POLYNOMIAL APPROXIMATIONS
The tangent line approximation Lsxd is the best first-degree (linear) approximation to f sxd
near x − a because f sxd and Lsxd have the same rate of change (derivative) at a. For a better
approximation than a linear one, let’s try a second-degree (quadratic) approximation Psxd. In
other words, we approximate a curve by a parabola instead of by a straight line. To make sure
that the approximation is a good one, we stipulate the following:
(i) Psad − f sad
(P and f should have the same value at a.)
(ii) P9sad − f 9sad
(P and f should have the same rate of change at a.)
(iii) P99sad − f 99sad
(The slopes of P and f should change at the same rate at a.)
1. Find the quadratic approximation Psxd − A 1 Bx 1 Cx 2 to the function f sxd − cos x that
satisfies conditions (i), (ii), and (iii) with a − 0. Graph P, f , and the linear approximation
Lsxd − 1 on a common screen. Comment on how well the functions P and L approximate f .
2. Determine the values of x for which the quadratic approximation f sxd < Psxd in Problem 1
is accurate to within 0.1. [Hint: Graph y − Psxd, y − cos x 2 0.1, and y − cos x 1 0.1
on a common screen.]
3. To approximate a function f by a quadratic function P near a number a, it is best to write P
in the form
Psxd − A 1 Bsx 2 ad 1 Csx 2 ad2
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SECTION 3.11
Hyperbolic Functions
261
Show that the quadratic function that satisfies conditions (i), (ii), and (iii) is
Psxd − f sad 1 f 9sadsx 2 ad 1 12 f 99sadsx 2 ad2
4. Find the quadratic approximation to f sxd − sx 1 3 near a − 1. Graph f , the quadratic
approximation, and the linear approximation from Example 3.10.2 on a common screen.
What do you conclude?
5. Instead of being satisfied with a linear or quadratic approximation to f sxd near x − a,
let’s try to find better approximations with higher-degree polynomials. We look for an
nth-degree polynomial
Tnsxd − c0 1 c1 sx 2 ad 1 c2 sx 2 ad2 1 c3 sx 2 ad3 1 ∙ ∙ ∙ 1 cn sx 2 adn
such that Tn and its first n derivatives have the same values at x − a as f and its first n
derivatives. By differentiating repeatedly and setting x − a, show that these conditions are
satisfied if c0 − f sad, c1 − f 9sad, c2 − 12 f 99 sad, and in general
ck −
f skdsad
k!
where k! − 1 ? 2 ? 3 ? 4 ? ∙ ∙ ∙ ? k. The resulting polynomial
Tn sxd − f sad 1 f 9sadsx 2 ad 1
f 99sad
f sndsad
sx 2 ad2 1 ∙ ∙ ∙ 1
sx 2 adn
2!
n!
is called the nth-degree Taylor polynomial of f centered at a. (We will study Taylor
polynomials in more detail in Chapter 11.)
6. Find the 8th-degree Taylor polynomial centered at a − 0 for the function f sxd − cos x.
Graph f together with the Taylor polynomials T2 , T4 , T6 , T8 in the viewing rectangle
f25, 5g by f21.4, 1.4g and comment on how well they approximate f .
3.11
Hyperbolic Functions
■ Hyperbolic Functions and Their Derivatives
Certain combinations of the exponential functions e x and e2x arise so frequently in mathematics and its applications that they deserve to be given special names. In many ways they
are analogous to the trigonometric functions, and they have the same relationship to the
hyperbola that the trigonometric functions have to the circle. For this reason they are collectively called hyperbolic functions and individually called hyperbolic sine, hyperbolic cosine, and so on.
Definition of the Hyperbolic Functions
e x 2 e2x
sinh x −
2
csch x −
1
sinh x
cosh x −
e x 1 e2x
2
sech x −
1
cosh x
tanh x −
sinh x
cosh x
coth x −
cosh x
sinh x
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262
CHAPTER 3
Differentiation Rules
The graphs of hyperbolic sine and hyperbolic cosine can be sketched using graphical
addition as in Figures 1 and 2.
y
y
y
y=cosh x
1
y= 2 ´
y=sinh x
0
y=1
x
1
y= 2 e–®
1
y=_ 2 e–®
1
1
0
FIGURE 1
FIGURE 3
y − cosh x − 12 e x 1 12 e 2x
y
0
x
y − tanh x
Note that sinh has domain R and range R, whereas cosh has domain R and range
f1, `d. The graph of tanh is shown in Figure 3. It has horizontal asymptotes y − 61. (See
Exercise 27.)
Some of the mathematical uses of hyperbolic functions will be seen in Chapter 7.
Applications to science and engineering occur whenever an entity such as light, velocity,
electricity, or radioactivity is gradually absorbed or extinguished because the decay can
be represented by hyperbolic functions. The most famous application is the use of hyperbolic cosine to describe the shape of a hanging wire. It can be proved that if a heavy
flexible cable (such as an overhead power line) is suspended between two points at the
same height, then it takes the shape of a curve with equation
y − c 1 a coshsxyad
FIGURE 4
A catenary y − c 1 a coshsxyad
called a catenary (see Figure 4). (The Latin word catena means “chain.”)
Another application of hyperbolic functions occurs in the description of ocean waves:
the velocity of a water wave with length L moving across a body of water with depth d is
modeled by the function
L
d
v−
FIGURE 5
Idealized water wave
x
y=_1
x
FIGURE 2
y − sinh x − 12 e x 2 12 e 2x
0
y= 2 ´
Î
S D
tL
2!d
tanh
2!
L
where t is the acceleration due to gravity (see Figure 5 and Exercise 57).
The hyperbolic functions satisfy a number of identities that are similar to well-known
trigonometric identities. We list some of them here and leave most of the proofs to the
exercises.
Hyperbolic Identities
sinhs2xd − 2sinh x
coshs2xd − cosh x
cosh2x 2 sinh2x − 1
1 2 tanh2x − sech2x
sinhsx 1 yd − sinh x cosh y 1 cosh x sinh y
coshsx 1 yd − cosh x cosh y 1 sinh x sinh y
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SECTION 3.11
Hyperbolic Functions
263
EXAMPLE 1 Prove (a) cosh2x 2 sinh2x − 1 and (b) 1 2 tanh2x − sech2x.
SOLUTION
iStock.com / gnagel
(a) cosh2x 2 sinh2x −
S
e x 1 e2x
2
D S
2
2
e x 2 e2x
2
D
2
−
e 2x 1 2 1 e22x
e 2x 2 2 1 e22x
2
4
4
−
4
−1
4
(b) We start with the identity proved in part (a):
cosh2x 2 sinh2x − 1
The Gateway Arch in St. Louis was
designed using a hyperbolic cosine
function (see Exercise 56).
If we divide both sides by cosh2x, we get
12
or
y
P(cos t, sin t)
O
Q
x
≈ +¥=1
FIGURE 6
y
P(cosh t, sinh t)
1 2 tanh2x − sech2x
≈-¥=1
FIGURE 7
x
n
The identity proved in Example 1(a) gives a clue to the reason for the name “hyperbolic” functions:
If t is any real number, then the point Pscos t, sin td lies on the unit circle x 2 1 y 2 − 1
because cos2t 1 sin2t − 1. In fact, t can be interpreted as the radian measure of /POQ
in Figure 6. For this reason the trigonometric functions are sometimes called circular
functions.
Likewise, if t is any real number, then the point Pscosh t, sinh td lies on the right
branch of the hyperbola x 2 2 y 2 − 1 because cosh2t 2 sinh2t − 1 and cosh t > 1. This
time, t does not represent the measure of an angle. However, it turns out that t represents
twice the area of the shaded hyperbolic sector in Figure 7, just as in the trigonometric
case t represents twice the area of the shaded circular sector in Figure 6.
The derivatives of the hyperbolic functions are easily computed. For example,
d
d
ssinh xd −
dx
dx
0
sinh2x
1
2 −
cosh x
cosh2x
S
e x 2 e2x
2
D
−
e x 1 e2x
− cosh x
2
We list the differentiation formulas for the hyperbolic functions as Table 1. The remaining proofs are left as exercises. Note the analogy with the differentiation formulas for
trigonometric functions, but note that the signs are different in some cases.
1 Derivatives of Hyperbolic Functions
d
d
ssinh xd − cosh x
scsch xd − 2csch x coth x
dx
dx
d
scosh xd − sinh x
dx
d
ssech xd − 2sech x tanh x
dx
d
stanh xd − sech2 x
dx
d
scoth xd − 2csch2 x
dx
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264
CHAPTER 3
Differentiation Rules
Any of these differentiation rules can be combined with the Chain Rule, as in the next
example.
EXAMPLE 2 If y − cosh sx , find dyydx .
SOLUTION Using (1) and the Chain Rule, we have
dy
d
d
sinh sx
−
(cosh sx ) − sinh sx ! dx sx −
dx
dx
2sx
n
■ Inverse Hyperbolic Functions and Their Derivatives
You can see from Figures 1 and 3 that sinh and tanh are one-to-one functions and so they
have inverse functions denoted by sinh21 and tanh21. Figure 2 shows that cosh is not oneto-one, but if we restrict the domain to the interval f0, `d, then the function y − cosh x
is one-to-one and attains all the values in its range f1, `d. The inverse hyperbolic cosine
function is defined as the inverse of this restricted function.
y − sinh21x
2
&? sinh y − x
y − cosh x &? cosh y − x and y > 0
21
y − tanh21x
&? tanh y − x
The remaining inverse hyperbolic functions are defined similarly (see Exercise 32).
We sketch the graphs of sinh21, cosh21, and tanh21 in Figures 8, 9, and 10 by referring
to Figures 1, 2, and 3.
y
y
y
0
x
_1
0
FIGURE 8 y − sinh 21 x
domain − R range − R
0
1
x
x
1
FIGURE 9 y − cosh 21 x
domain − f1, `d range − f0, `d
FIGURE 10 y − tanh 21 x
domain − s21, 1d range − R
Since the hyperbolic functions are defined in terms of exponential functions, it’s not
surprising to learn that the inverse hyperbolic functions can be expressed in terms of
logarithms. In particular, we have:
Formula 3 is proved in Example 3.
The proofs of Formulas 4 and 5 are
requested in Exercises 30 and 31.
3
sinh21x − ln( x 1 sx 2 1 1 )
x[R
4
cosh21x − ln( x 1 sx 2 2 1 )
x>1
5
tanh21x − 12 ln
S D
11x
12x
21 , x , 1
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SECTION 3.11
Hyperbolic Functions
265
EXAMPLE 3 Show that sinh21x − ln( x 1 sx 2 1 1 ).
SOLUTION Let y − sinh21x. Then
x − sinh y −
e y 2 e2y
2
so
e y 2 2x 2 e2y − 0
or, multiplying by e y,
e 2y 2 2xe y 2 1 − 0
This is really a quadratic equation in e y:
se y d2 2 2xse y d 2 1 − 0
Solving by the quadratic formula, we get
ey −
2x 6 s4x 2 1 4
− x 6 sx 2 1 1
2
Note that e y . 0, but x 2 sx 2 1 1 , 0 (because x , sx 2 1 1 ). Thus the minus sign
is inadmissible and we have
e y − x 1 sx 2 1 1
Therefore
y − lnse y d − ln( x 1 sx 2 1 1 )
This shows that
sinh21x − ln( x 1 sx 2 1 1 )
(See Exercise 29 for another method.)
Notice that the formulas for the
derivatives of tanh21x and coth21x
appear to be identical. But the
domains of these functions have no
numbers in common: tanh21x is
defined for x , 1, whereas coth21x
is defined for x . 1.
| |
| |
n
6 Derivatives of Inverse Hyperbolic Functions
d
1
d
1
ssinh21xd −
scsch21xd − 2
2
dx
dx
x sx 2 1 1
s1 1 x
| |
d
1
scosh21xd −
2
dx
sx 2 1
d
1
ssech21xd − 2
dx
x s1 2 x 2
d
1
stanh21xd −
dx
1 2 x2
d
1
scoth21xd −
dx
1 2 x2
The inverse hyperbolic functions are all differentiable because the hyperbolic functions are differentiable (see Appendix F ). The formulas in Table 6 can be proved either
by the method for inverse functions or by differentiating Formulas 3, 4, and 5.
EXAMPLE 4 Prove that
d
1
ssinh21xd −
.
dx
s1 1 x 2
SOLUTION 1 Let y − sinh21x. Then sinh y − x. If we differentiate this equation
implicitly with respect to x, we get
cosh y
dy
−1
dx
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266
CHAPTER 3
Differentiation Rules
Since cosh2 y 2 sinh2 y − 1 and cosh y > 0, we have cosh y − s1 1 sinh2 y , so
dy
1
1
1
−
−
−
2
dx
cosh y
s1 1 sinh y
s1 1 x 2
SOLUTION 2 From Equation 3 (proved in Example 3), we have
d
d
ssinh21xd −
ln( x 1 sx 2 1 1 )
dx
dx
−
−
−
−
EXAMPLE 5 Find
1
d
( x 1 sx 2 1 1 )
dx
x 1 sx 1 1
2
1
x 1 sx 1 1
2
S
11
x
sx 1 1
2
D
sx 2 1 1 1 x
(x 1 sx 2 1 1 )sx 2 1 1
1
sx 1 1
2
n
d
ftanh21ssin xdg.
dx
SOLUTION Using Table 6 and the Chain Rule, we have
d
1
d
ftanh21ssin xdg −
ssin xd
dx
1 2 ssin xd2 dx
−
3.11
1
cos x
− sec x
2 cos x −
1 2 sin x
cos2x
n
Exercises
1–6 Find the numerical value of each expression.
9. Write sinhsln xd as a rational function of x.
1. (a) sinh 0
(b) cosh 0
10. Write coshs4 ln xd as a rational function of x .
2. (a) tanh 0
(b) tanh 1
11–23 Prove the identity.
3. (a) coshsln 5d
(b) cosh 5
4. (a) sinh 4
(b) sinhsln 4d
11. sinhs2xd − 2sinh x
(This shows that sinh is an odd function.)
5. (a) sech 0
(b) cosh21 1
12. coshs2xd − cosh x
(This shows that cosh is an even function.)
6. (a) sinh 1
(b) sinh21 1
13. cosh x 1 sinh x − e x
14. cosh x 2 sinh x − e2x
x
7. Write 8 sinh x 1 5 cosh x in terms of e and e .
15. sinhsx 1 yd − sinh x cosh y 1 cosh x sinh y
8. Write 2e 2x 1 3e22x in terms of sinh 2x and cosh 2x.
16. coshsx 1 yd − cosh x cosh y 1 sinh x sinh y
2x
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SECTION 3.11
tanh x 1 tanh y
1 1 tanh x tanh y
34. Prove the formula given in Table 6 for the derivative of each
of the following functions.
(a) sech21
(b) csch21
19. sinh 2x − 2 sinh x cosh x
20. cosh 2x − cosh 2 x 1 sinh 2 x
21. tanhsln xd −
35–53 Find the derivative. Simplify where possible.
x2 2 1
x2 1 1
35. f sxd − cosh 3x
36. f sxd − e x cosh x
37. hsxd − sinhsx 2 d
38. tsxd − sinh 2 x
23. scosh x 1 sinh xdn − cosh nx 1 sinh nx
(n any real number)
39. Gstd − sinhsln td
40. Fstd − lnssinh td
41. f sxd − tanhsx
42. Hsvd − e tanh 2v
24. If tanh x − 12
13 , find the values of the other hyperbolic functions at x.
43. y − sech x tanh x
44. y − sechstanh xd
45. tstd − t coth st 2 1 1
46. f std −
47. f sxd − sinh21s22xd
48. tsxd − tanh21sx 3 d
22.
1 1 tanh x
− e 2x
1 2 tanh x
25. If cosh x − 53 and x . 0, find the values of the other hyperbolic functions at x.
26. (a) Use the graphs of sinh, cosh, and tanh in Figures 1–3 to
draw the graphs of csch, sech, and coth.
(b) Check the graphs that you sketched in part (a) by using
;
a graphing calculator or computer to produce them.
27. Use the definitions of the hyperbolic functions to find each
of the following limits.
(a) lim tanh x
(b) lim tanh x
xl`
(d)
(e) lim sech x
(f ) lim coth x
(g) lim1 coth x
(h) lim2 coth x
(i)
sinh x
( j) lim
xl`
ex
xl`
49. y − cosh21ssec "d,
0 ⩽ " , !y2
50. y − sech21ssin "d,
0 , " , !y2
51. Gsud − cosh21s1 1 u 2 ,
1 1 sinh t
1 2 sinh t
u.0
52. y − x tanh21x 1 lns1 2 x 2
x l2`
(c) lim sinh x
xl`
lim sinh x
x l2`
53. y − x sinh21sxy3d 2 s9 1 x 2
xl`
Î
1 1 tanh x
− 12 e xy2.
1 2 tanh x
54. Show that
d
dx
28. Prove the formulas given in Table 1 for the derivatives of the
functions (a) cosh, (b) tanh, (c) csch, (d) sech, and (e) coth.
55. Show that
d
arctanstanh xd − sech 2x.
dx
29. Give an alternative solution to Example 3 by letting
y − sinh21x and then using Exercise 13 and Example 1(a)
with x replaced by y.
56. The Gateway Arch The Gateway Arch in St. Louis was
designed by Eero Saarinen and was constructed using
the equation
x l0
lim csch x
x l2`
267
33. Prove the formula given in Table 6 for the derivative of each
of the following functions.
(a) cosh21
(b) tanh21
(c) coth21
17. coth2x 2 1 − csch2x
18. tanhsx 1 yd −
Hyperbolic Functions
x l0
y − 211.49 2 20.96 cosh 0.03291765x
30. Prove Equation 4.
31. Prove Equation 5 using (a) the method of Example 3 and
(b) Exercise 22 with x replaced by y.
32. For each of the following functions (i) give a definition like
those in (2), (ii) sketch the graph, and (iii) find a formula
similar to Equation 3.
(a) csch 21
(b) sech21
(c) coth21
4
;
for the central curve of the arch, where x and y are measured in meters and x < 91.20.
(a) Graph the central curve.
(b) What is the height of the arch at its center?
(c) At what points is the height 100 m?
(d) What is the slope of the arch at the points in
part (c)?
| |
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268
CHAPTER 3
Differentiation Rules
57. If a water wave with length L moves with velocity v in a
body of water with depth d, then
v−
Î
S D
tL
2!d
tanh
2!
L
where t is the acceleration due to gravity. (See Figure 5.)
Explain why the approximation
v<
Î
tL
2!
; 58. A flexible cable always hangs in the shape of a catenary
y − c 1 a coshsxyad, where c and a are constants and
a . 0 (see Figure 4 and Exercise 60). Graph several members of the family of functions y − a coshsxyad. How does
the graph change as a varies?
59. A telephone line hangs between two poles 14 m apart in the
shape of the catenary y − 20 coshsxy20d 2 15, where x and
y are measured in meters.
(a) Find the slope of this curve where it meets the righthand pole.
(b) Find the angle " between the line and the pole.
0
7
x
60. Using principles from physics it can be shown that when a
cable is hung between two poles, it takes the shape of a
curve y − f sxd that satisfies the differential equation
Î S D
11
dy
dx
2
where ' is the linear density of the cable, t is the acceleration due to gravity, T is the tension in the cable at its lowest
point, and the coordinate system is chosen appropriately.
Verify that the function
y − f sxd −
SÎ D
mt
tanh t
k
tk
m
where m is the mass of the object, t − 9.8 mys 2 is the acceleration due to gravity, k is a constant, t is measured in seconds, and v in mys.
(a) Calculate the terminal velocity of the object, that is,
lim tl` v std.
(b) If a person skydives from a plane, the value of the
constant k depends on his or her position. For a “belly-toearth” position, k − 0.515 kgys, but for a “feet-first”
position, k − 0.067 kgys. If a 60-kg person descends in
belly-to-earth position, what is the terminal velocity?
What about feet-first?
Source: L. Long et al., “How Terminal Is Terminal Velocity?” American
Mathematical Monthly 113 (2006): 752–55.
y − A sinh mx 1 B cosh mx
¨
5
't
d y
−
dx 2
T
Î
63. (a) Show that any function of the form
y
2
62. A model for the velocity of a falling object after time t is
v std −
is appropriate in deep water.
_7
61. A cable with linear density ' − 2 kgym is strung from the
tops of two poles that are 200 m apart.
(a) Use Exercise 60 to find the tension T so that the cable is
60 m above the ground at its lowest point. How tall are
the poles?
(b) If the tension is doubled, what is the new low point of the
cable? How tall are the poles now?
S D
T
'tx
cosh
't
T
is a solution of this differential equation.
satisfies the differential equation y99 − m 2 y.
(b) Find y − ysxd such that y99 − 9y, ys0d − 24,
and y9s0d − 6.
64. If x − lnssec " 1 tan "d, show that sec " − cosh x.
65. At what point of the curve y − cosh x does the tangent have
slope 1?
; 66. Investigate the family of functions
f n sxd − tanhsn sin xd
where n is a positive integer. Describe what happens to the
graph of f n when n becomes large.
67. Show that if a ± 0 and b ± 0, then there exist numbers $
and ( such that ae x 1 be2x equals either
$ sinhsx 1 (d
or
$ coshsx 1 (d
In other words, almost every function of the form
f sxd − ae x 1 be2x is a shifted and stretched hyperbolic sine
or hyperbolic cosine function.
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CHAPTER 3
3
Review
269
REVIEW
CONCEPT CHECK
Answers to the Concept Check are available at StewartCalculus.com.
1. State each differentiation rule both in symbols and in words.
(a) The Power Rule
(b) The Constant Multiple Rule
(c) The Sum Rule
(d) The Difference Rule
(e) The Product Rule
(f ) The Quotient Rule
(g) The Chain Rule
(d) Why is the natural logarithmic function y − ln x used
more often in calculus than the other logarithmic functions y − log b x ?
2. State the derivative of each function.
(a) y − x n
(b) y − e x
(d) y − ln x
(e) y − log b x
(g) y − cos x
(h) y − tan x
( j) y − sec x
(k) y − cot x
(m) y − cos21x
(n) y − tan21x
( p) y − cosh x
(q) y − tanh x
(s) y − cosh21x
(t) y − tanh21x
(c) y − b x
(f ) y − sin x
(i) y − csc x
(l) y − sin21x
(o) y − sinh x
(r) y − sinh21x
3. (a) How is the number e defined?
(b) Express e as a limit.
(c) Why is the natural exponential function y − e x used more
often in calculus than the other exponential functions y − b x?
4. (a) Explain how implicit differentiation works.
(b) Explain how logarithmic differentiation works.
5. Give several examples of how the derivative can be interpreted as a rate of change in physics, chemistry, biology,
economics, or other sciences.
6. (a) Write a differential equation that expresses the law of
natural growth.
(b) Under what circumstances is this an appropriate model
for population growth?
(c) What are the solutions of this equation?
7. (a) Write an expression for the linearization of f at a.
(b) If y − f sxd, write an expression for the differential dy.
(c) If dx − Dx, draw a picture showing the geometric
meanings of Dy and dy.
TRUE-FALSE QUIZ
Determine whether the statement is true or false. If it is true,
explain why. If it is false, explain why or give an example that
disproves the statement.
7.
d
s10 x d − x10 x21
dx
1. If f and t are differentiable, then
8.
d
1
sln 10d −
dx
10
9.
d
d
stan2xd −
ssec 2xd
dx
dx
10.
d
x 2 1 x − 2x 1 1
dx
d
f f sxd 1 tsxdg − f 9sxd 1 t9sxd
dx
2. If f and t are differentiable, then
d
f f sxd tsxdg − f 9sxd t9sxd
dx
3. If f and t are differentiable, then
d
f s tsxdd − f 9s tsxdd t9sxd
dx
f
g
4. If f is differentiable, then
d
f 9sxd
.
sf sxd −
dx
2 sf sxd
5. If f is differentiable, then
d
f 9sxd
f (sx ) −
.
dx
2 sx
6. If y − e 2, then y9 − 2e.
|
| |
|
11. The derivative of a polynomial is a polynomial.
12. If f sxd − sx 6 2 x 4 d 5, then f s31dsxd − 0.
13. The derivative of a rational function is a rational function.
14. An equation of the tangent line to the parabola y − x 2
at s22, 4d is y 2 4 − 2xsx 1 2d.
15. If tsxd − x 5, then lim
xl2
tsxd 2 ts2d
− 80.
x22
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
270
CHAPTER 3
Differentiation Rules
EXERCISES
1–54 Calculate y9.
1. y − sx 2 1 x 3 d4
2. y −
2
3. y −
x 2x12
4. y −
sx
5. y − x 2 sin ! x
7. y −
1
sx
2
1
5
x3
s
tan x
1 1 cos x
48. y −
sin mx
x
49. y − lnscosh 3xd
Z
x2 2 4
2x 1 5
Z
51. y − cosh21ssinh xd
53. y − cos(e stan 3x )
54. y − sin2 (cosssin !x )
mx
10. y − e cos nx
11. y − sx cos sx
12. y − sarcsin 2xd 2
e 1yx
x2
55. If f std − s4t 1 1, find f 99s2d.
56. If ts"d − " sin ", find t99s!y6d.
14. y − ln sec x
S
u21
u2 1 u 1 1
15. y 1 x cos y − x 2 y
16. y −
17. y − sarctan x
18. y − cotscsc xd
S D
19. y − tan
47. y − x sinhsx 2 d
52. y − x tanh21sx
8. xe y − y sin x
9. y − lnsx ln xd
13. y −
sx 1 *d4
x 4 1 *4
50. y − ln
6. y − x cos21 x
t4 2 1
t4 1 1
46. y −
t
1 1 t2
D
4
20. y − e x sec x
57. Find y99 if x 6 1 y 6 − 1.
58. Find f sndsxd if f sxd − 1ys2 2 xd.
59. Use mathematical induction to show that if f sxd − xe x,
then f sndsxd − sx 1 nde x. (Note: See Principles of Problem
Solving following Chapter 1.)
t3
.
t l 0 tan3s2td
60. Evaluate lim
21. y − 3 x ln x
22. y − secs1 1 x 2 d
23. y − s1 2 x 21 d21
3
24. y − 1ys
x 1 sx
25. sinsxyd − x 2 2 y
26. y − ssin s x
27. y − log 5 s1 1 2xd
28. y − scos xd x
29. y − ln sin x 2 12 sin2x
30. y −
31. y − x tan21s4xd
32. y − e cos x 1 cosse x d
64–65 Find equations of the tangent line and normal line to the
curve at the given point.
34. y − 10 tan !"
64. x 2 1 4xy 1 y 2 − 13,
35. y − cots3x 2 1 5d
36. y − st lnst 4d
65. y − s2 1 xde2x,
37. y − sin(tan s1 1 x 3 )
38. y − x sec21x
|
33. y − ln sec 5x 1 tan 5x
|
sx 2 1 1d 4
s2x 1 1d 3s3x 2 1d 5
39. y − 5 arctan s1yxd
40. y − sin21scos "d,
0,",!
41. y − x tan21x 2 12 lns1 1 x 2 d
42. y − lnsarcsin x 2 d
43. y − tan2ssin "d
44. y 1 ln y − xy 2
45. y −
sx 1 1 s2 2 xd5
sx 1 3d7
61–63 Find an equation of the tangent line to the curve at the
given point.
61. y − 4 sin2 x, s!y6, 1d
63. y − s1 1 4 sin x ,
62. y −
x2 2 1
, s0, 21d
x2 1 1
s0, 1d
s2, 1d
s0, 2d
; 66. If f sxd − xe , find f 9sxd. Graph f and f 9 on the same
screen and comment.
sin x
67. (a) If f sxd − x s5 2 x , find f 9sxd.
(b) Find equations of the tangent lines to the curve
y − x s5 2 x at the points s1, 2d and s4, 4d.
(c) Illustrate part (b) by graphing the curve and tangent lines
;
on the same screen.
(d) Check to see that your answer to part (a) is reasonable by
;
comparing the graphs of f and f 9.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CHAPTER 3
68. (a) If f sxd − 4x 2 tan x, 2!y2 , x , !y2, find f 9
and f 99.
(b) Check to see that your answers to part (a) are reason;
able by comparing the graphs of f , f 9, and f 99.
69. At what points on the curve y − sin x 1 cos x,
0 < x < 2!, is the tangent line horizontal?
2
79. f sxd − tse x d
|
81. f sxd − ln tsxd
83. hsxd −
70. Find the points on the ellipse x 1 2y − 1 where the
tangent line has slope 1.
84. hsxd −
f 9sxd
1
1
1
−
1
1
f sxd
x2a
x2b
x2c
72. (a) By differentiating the double-angle formula
cos 2x − cos2x 2 sin2x
obtain the double-angle formula for the sine function.
(b) By differentiating the addition formula
sinsx 1 ad − sin x cos a 1 cos x sin a
obtain the addition formula for the cosine function.
73. Suppose that
271
80. f sxd − e tsxd
|
82. f sxd − tsln xd
83–85 Find h9 in terms of f 9 and t9.
2
71. If f sxd − sx 2 adsx 2 bdsx 2 cd, show that
Review
f sxd tsxd
f sxd 1 tsxd
Î
f sxd
tsxd
85. hsxd − f s tssin 4xdd
; 86. (a) Graph the function f sxd − x 2 2 sin x in the viewing
rectangle f0, 8g by f22, 8g.
(b) On which interval is the average rate of change larger:
f1, 2g or f2, 3g?
(c) At which value of x is the instantaneous rate of change
larger: x − 2 or x − 5?
(d) Check your visual estimates in part (c) by computing
f 9sxd and comparing the numerical values of f 9s2d
and f 9s5d.
87. At what point on the curve
y − flnsx 1 4dg 2
f s1d − 2
f 9s1d − 3
f s2d − 1
f 9s2d − 2
ts1d − 3
t9s1d − 1
ts2d − 1
t9s2d − 4
(a) If Ssxd − f sxd 1 tsxd, find S9s1d.
(b) If Psxd − f sxd tsxd, find P9s2d.
(c) If Qsxd − f sxdytsxd, find Q9s1d.
(d) If Csxd − f stsxdd, find C9s2d.
74. If f and t are the functions whose graphs are shown, let
Psxd − f sxd tsxd, Qsxd − f sxdytsxd, and Csxd − f s tsxdd.
Find (a) P9s2d, (b) Q9s2d, and (c) C9s2d.
y
g
f
1
0
1
x
75–82 Find f 9 in terms of t9.
75. f sxd − x 2tsxd
76. f sxd − tsx 2 d
77. f sxd − f tsxdg 2
78. f sxd − ts tsxdd
is the tangent horizontal?
88. (a) Find an equation of the tangent line to the curve y − e x
that is parallel to the line x 2 4y − 1.
(b) Find an equation of the tangent to the curve y − e x that
passes through the origin.
89. Find a parabola y − ax 2 1 bx 1 c that passes through the
point s1, 4d and whose tangent lines at x − 21 and x − 5
have slopes 6 and 22, respectively.
90. The function Cstd − Kse2at 2 e2bt d, where a, b, and K are
positive constants and b . a, is used to model the concentration at time t of a drug injected into the bloodstream.
(a) Show that lim t l ` Cstd − 0.
(b) Find C9std, the rate of change of drug concentration in
the blood.
(c) When is this rate equal to 0?
91. An equation of motion of the form s − Ae2ct coss%t 1 &d
represents damped oscillation of an object. Find the velocity
and acceleration of the object.
92. A particle moves along a horizontal line so that its coordinate at time t is x − sb 2 1 c 2 t 2 , t > 0, where b and c
are positive constants.
(a) Find the velocity and acceleration functions.
(b) Show that the particle always moves in the positive
direction.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
272
CHAPTER 3
Differentiation Rules
93. A particle moves on a vertical line so that its coordinate at
time t is y − t 3 2 12t 1 3, t > 0.
(a) Find the velocity and acceleration functions.
(b) When is the particle moving upward and when is it
moving downward?
(c) Find the distance that the particle travels in the time
interval 0 < t < 3.
(d) Graph the position, velocity, and acceleration functions
;
for 0 < t < 3.
(e) When is the particle speeding up? When is it slowing
down?
94.
The volume of a right circular cone is V − 13 !r 2h, where
r is the radius of the base and h is the height.
(a) Find the rate of change of the volume with respect to
the height if the radius is constant.
(b) Find the rate of change of the volume with respect to
the radius if the height is constant.
95. The mass of part of a wire is x (1 1 sx ) kilograms, where
x is measured in meters from one end of the wire. Find the
linear density of the wire when x − 4 m.
96. The cost, in dollars, of producing x units of a certain commodity is
100. A cup of hot chocolate has temperature 80°C in a room
kept at 20°C. After half an hour the hot chocolate cools
to 60°C.
(a) What is the temperature of the chocolate after another
half hour?
(b) When will the chocolate have cooled to 40°C?
101. The volume of a cube is increasing at a rate of 10 cm3ymin.
How fast is the surface area increasing when the length of
an edge is 30 cm?
102. A paper cup has the shape of a cone with height 10 cm and
radius 3 cm (at the top). If water is poured into the cup at a
rate of 2 cm3ys, how fast is the water level rising when the
water is 5 cm deep?
103. A balloon is rising at a constant speed of 5 ftys. A boy is
cycling along a straight road at a speed of 15 ftys. When he
passes under the balloon, it is 45 ft above him. How fast is
the distance between the boy and the balloon increasing 3 s
later?
104. A waterskier skis over the ramp shown in the figure at a
speed of 30 ftys. How fast is she rising as she leaves the
ramp?
Csxd − 920 1 2x 2 0.02x 2 1 0.00007x 3
(a) Find the marginal cost function.
(b) Find C9s100d and explain its meaning.
(c) Compare C9s100d with the cost of producing the 101st
item.
97. A bacteria culture contains 200 cells initially and grows at a
rate proportional to its size. After half an hour the population has increased to 360 cells.
(a) Find the number of cells after t hours.
(b) Find the number of cells after 4 hours.
(c) Find the rate of growth after 4 hours.
(d) When will the population reach 10,000?
98. Cobalt-60 has a half-life of 5.24 years.
(a) Find the mass that remains from a 100-mg sample after
20 years.
(b) How long would it take for the mass to decay to 1 mg?
99. Let Cstd be the concentration of a drug in the bloodstream.
As the body eliminates the drug, Cstd decreases at a rate that
is proportional to the amount of the drug that is present at
the time. Thus C9std − 2kCstd, where k is a positive number
called the elimination constant of the drug.
(a) If C0 is the concentration at time t − 0, find the
concentration at time t.
(b) If the body eliminates half the drug in 30 hours, how
long does it take to eliminate 90% of the drug?
4 ft
15 ft
105. The angle of elevation of the sun is decreasing at a rate of
0.25 radyh. How fast is the shadow cast by a 400-ft-tall
building increasing when the angle of elevation of the sun
is !y6?
; 106. (a) Find the linear approximation to f sxd − s25 2 x 2
near 3.
(b) Illustrate part (a) by graphing f and the linear
approximation.
(c) For what values of x is the linear approximation
accurate to within 0.1?
3
107. (a) Find the linearization of f sxd − s
1 1 3x at a − 0.
State the corresponding linear approximation and use
3
it to give an approximate value for s
1.03 .
(b)
Determine
the
values
of
x
for
which
the linear
;
approximation given in part (a) is accurate to
within 0.1.
108. Evaluate dy if y − x 3 2 2x 2 1 1, x − 2, and dx − 0.2.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CHAPTER 3
109. A window has the shape of a square surmounted by a semicircle. The base of the window is measured as having width
60 cm with a possible error in measurement of 0.1 cm. Use
differentials to estimate the maximum error possible in computing the area of the window.
110–112 Express the limit as a derivative and evaluate.
17
110. lim
x l1
x 21
x21
4
16 1 h 2 2
s
hl0
h
111. lim
113. Evaluate lim
xl0
Review
273
s1 1 tan x 2 s1 1 sin x
.
x3
114. Suppose f is a differentiable function such that f s tsxdd − x
and f 9sxd − 1 1 f f sxdg 2. Show that t9sxd − 1ys1 1 x 2 d.
115. Find f 9sxd if it is known that
d
f f s2xdg − x 2
dx
112.
lim
"l!y3
cos " 2 0.5
" 2 !y3
116. Show that the length of the portion of any tangent line to the
astroid x 2y3 1 y 2y3 − a 2y3 cut off by the coordinate axes is
constant.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Problems Plus
Try to solve the following examples yourself before reading the solutions.
EXAMPLE 1 How many lines are tangent to both of the parabolas y − 21 2 x 2 and
y − 1 1 x 2 ? Find the coordinates of the points at which these tangents touch the
parabolas.
y
SOLUTION To gain insight into this problem, it is essential to draw a diagram. So we
sketch the parabolas y − 1 1 x 2 (which is the standard parabola y − x 2 shifted 1 unit
upward) and y − 21 2 x 2 (which is obtained by reflecting the first parabola about the
x-axis). If we try to draw a line tangent to both parabolas, we soon discover that there
are only two possibilities, as illustrated in Figure 1.
Let P be a point at which one of these tangents touches the upper parabola and let a
be its x-coordinate. (The choice of notation for the unknown is important. Of course we
could have used b or c or x 0 or x1 instead of a. However, it’s not advisable to use x in
place of a because that x could be confused with the variable x in the equation of the
parabola.) Then, since P lies on the parabola y − 1 1 x 2, its y-coordinate must be
1 1 a 2. Because of the symmetry shown in Figure 1, the coordinates of the point Q
where the tangent touches the lower parabola must be s2a, 2s1 1 a 2 dd.
To use the given information that the line is a tangent, we equate the slope of the
line PQ to the slope of the tangent line at P. We have
P
1
x
_1
Q
FIGURE 1
mPQ −
1 1 a 2 2 s21 2 a 2 d
1 1 a2
−
a 2 s2ad
a
If f sxd − 1 1 x 2, then the slope of the tangent line at P is f 9sad − 2a. Thus the condition that we need to use is that
1 1 a2
− 2a
a
y
3≈ ≈ 1 ≈
2
0.3≈
0.1≈
0
x
y=ln x
FIGURE 2
y
y=c≈
c=?
0
a
y=ln x
FIGURE 3
x
Solving this equation, we get 1 1 a 2 − 2a 2, so a 2 − 1 and a − 61. Therefore the
points are (1, 2) and s21, 22d. By symmetry, the two remaining points are s21, 2d
and s1, 22d.
n
EXAMPLE 2 For what values of c does the equation ln x − cx 2 have exactly one
solution?
SOLUTION One of the most important principles of problem solving is to draw a diagram, even if the problem as stated doesn’t explicitly mention a geometric situation.
Our present problem can be reformulated geometrically as follows: for what values of c
does the curve y − ln x intersect the curve y − cx 2 in exactly one point?
Let’s start by graphing y − ln x and y − cx 2 for various values of c. We know that,
for c ± 0, y − cx 2 is a parabola that opens upward if c . 0 and downward if c , 0.
Figure 2 shows the parabolas y − cx 2 for several positive values of c. Most of them
don’t intersect y − ln x at all and one intersects twice. We have the feeling that there
must be a value of c (somewhere between 0.1 and 0.3) for which the curves intersect
exactly once, as in Figure 3.
To find that particular value of c, we let a be the x-coordinate of the single point
of intersection. In other words, ln a − ca 2, so a is the unique solution of the given
equation. We see from Figure 3 that the curves just touch, so they have a common
tangent line when x − a. That means the curves y − ln x and y − cx 2 have the same
slope when x − a. Therefore
1
− 2ca
a
274
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Solving the equations ln a − ca 2 and 1ya − 2ca, we get
y
ln a − ca 2 − c !
y=ln x
Thus a − e 1y2 and
0
x
c−
1
1
−
2c
2
ln a
ln e 1y2
1
−
−
2
a
e
2e
For negative values of c we have the situation illustrated in Figure 4: all parabolas
y − cx 2 with negative values of c intersect y − ln x exactly once. And let’s not forget
about c − 0: the curve y − 0x 2 − 0 is just the x-axis, which intersects y − ln x
exactly once.
To summarize, the required values of c are c − 1ys2ed and c < 0.
n
FIGURE 4
Problems
1. Find points P and Q on the parabola y − 1 2 x 2 so that the triangle ABC formed by the
x-axis and the tangent lines at P and Q is an equilateral triangle (see the figure).
y
A
P
Q
0
B
C
x
3
2
; 2. Find the point where the curves y − x 2 3x 1 4 and y − 3sx 2 xd are tangent to each
other, that is, have a common tangent line. Illustrate by sketching both curves and the
common tangent.
3. Show that the tangent lines to the parabola y − ax 2 1 bx 1 c at any two points with
x-coordinates p and q must intersect at a point whose x-coordinate is halfway between p
and q.
4. Show that
d
dx
5. If f sxd − lim
tlx
S
sin2 x
cos2 x
1
1 1 cot x
1 1 tan x
D
− 2cos 2x.
sec t 2 sec x
, find the value of f 9s!y4d.
t2x
6. Find the values of the constants a and b such that
3
ax 1 b 2 2
5
s
−
xl0
x
12
y
lim
7. Show that sin21stanh xd − tan21ssinh xd.
x
FIGURE FOR PROBLEM 8
8. A car is traveling at night along a highway shaped like a parabola with its vertex at the origin
(see the figure). The car starts at a point 100 m west and 100 m north of the origin and
travels in an easterly direction. There is a statue located 100 m east and 50 m north of the
origin. At what point on the highway will the car’s headlights illuminate the statue?
9. Prove that
dn
ssin4 x 1 cos4 xd − 4n21 coss4x 1 n!y2d.
dx n
275
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10. If f is differentiable at a, where a . 0, evaluate the following limit in terms of f 9sad:
lim
xla
f sxd 2 f sad
sx 2 sa
11. The figure shows a circle with radius 1 inscribed in the parabola y − x 2. Find the center of
the circle.
y
1
y=≈
1
0
x
12. Find all values of c such that the parabolas y − 4x 2 and x − c 1 2y 2 intersect each other at
right angles.
13. How many lines are tangent to both of the circles x 2 1 y 2 − 4 and x 2 1 s y 2 3d 2 − 1?
At what points do these tangent lines touch the circles?
x 46 1 x 45 1 2
14. If f sxd −
, calculate f s46ds3d. Express your answer using factorial notation:
11x
n! − 1 ! 2 ! 3 ! ∙ ∙ ∙ ! sn 2 1d ! n
15. The figure shows a rotating wheel with radius 40 cm and a connecting rod AP with length
1.2 m. The pin P slides back and forth along the x-axis as the wheel rotates counterclockwise at a rate of 360 revolutions per minute.
(a) Find the angular velocity of the connecting rod, d$ydt, in radians per second,
when " − !y3.
(b) Express the distance x − OP in terms of ".
(c) Find an expression for the velocity of the pin P in terms of ".
|
|
y
A
O
å
¨
P (x, 0)
x
16. Tangent lines T1 and T2 are drawn at two points P1 and P2 on the parabola y − x 2 and they
intersect at a point P. Another tangent line T is drawn at a point between P1 and P2; it
intersects T1 at Q1 and T2 at Q2. Show that
17. Show that
| PQ | 1 | PQ | − 1
| PP | | PP |
1
2
1
2
dn
se ax sin bxd − r ne ax sinsbx 1 n"d
dx n
where a and b are positive numbers, r 2 − a 2 1 b 2, and " − tan21sbyad.
276
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e sin x 2 1
.
xl! x 2 !
18. Evaluate lim
19. Let T and N be the tangent and normal lines to the ellipse x 2y9 1 y 2y4 − 1 at any point P
on the ellipse in the first quadrant. Let x T and yT be the x- and y-intercepts of T and x N and
yN be the intercepts of N. As P moves along the ellipse in the first quadrant (but not on the
axes), what values can x T , yT , x N, and yN take on? First try to guess the answers just by
looking at the figure. Then use calculus to solve the problem and see how good your
intuition is.
y
yT
T
2
P
xN
0
xT
3
N
yN
x
sins3 1 xd2 2 sin 9
.
xl0
x
20. Evaluate lim
21. (a) Use the identity for tansx 2 yd (see Equation 15b in Appendix D) to show that if two
lines L 1 and L 2 intersect at an angle $, then
tan $ −
m 2 2 m1
1 1 m1 m 2
where m1 and m 2 are the slopes of L 1 and L 2, respectively.
(b) The angle between the curves C1 and C2 at a point of intersection P is defined to be
the angle between the tangent lines to C1 and C2 at P (if these tangent lines exist). Use
part (a) to find, correct to the nearest degree, the angle between each pair of curves at
each point of intersection.
(i) y − x 2 and y − sx 2 2d2
(ii) x 2 2 y 2 − 3 and x 2 2 4x 1 y 2 1 3 − 0
22. Let Psx 1, y1d be a point on the parabola y 2 − 4px with focus Fs p, 0d. Let $ be the angle
between the parabola and the line segment FP, and let ( be the angle between the horizontal line y − y1 and the parabola as in the figure. Prove that $ − (. (Thus, by a principle of
geometrical optics, light from a source placed at F will be reflected along a line parallel to
the x-axis. This explains why paraboloids, the surfaces obtained by rotating parabolas about
their axes, are used as the shape of some automobile headlights and mirrors for telescopes.)
y
0
å
∫
P(⁄, ›)
y=›
x
F( p, 0)
¥=4px
277
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Q
¨
A
R
P
¨
O
23. Suppose that we replace the parabolic mirror of Problem 22 by a spherical mirror. Although
the mirror has no focus, we can show the existence of an approximate focus. In the figure,
C is a semicircle with center O. A ray of light coming in toward the mirror parallel to the
axis along the line PQ will be reflected to the point R on the axis so that /PQO − /OQR
(the angle of incidence is equal to the angle of reflection). What happens to the point R as
P is taken closer and closer to the axis?
24. If f and t are differentiable functions with f s0d − ts0d − 0 and t9s0d ± 0, show that
C
lim
xl0
FIGURE FOR PROBLEM 23
25. Evaluate lim
xl0
f sxd
f 9s0d
−
tsxd
t9s0d
sinsa 1 2xd 2 2 sinsa 1 xd 1 sin a
.
x2
26. (a) The cubic function f sxd − xsx 2 2dsx 2 6d has three distinct zeros: 0, 2, and 6. Graph
f and its tangent lines at the average of each pair of zeros. What do you notice?
(b) Suppose the cubic function f sxd − sx 2 adsx 2 bdsx 2 cd has three distinct zeros:
a, b, and c. Prove, with the help of a computer algebra system, that a tangent line drawn
at the average of the zeros a and b intersects the graph of f at the third zero.
27. For what value of k does the equation e 2x − ksx have exactly one solution?
28. For which positive numbers a is it true that a x > 1 1 x for all x ?
29. If
y−
show that y9 −
x
sa 2 2 1
2
2
sa 2 2 1
arctan
sin x
a 1 sa 2 2 1 1 cos x
1
.
a 1 cos x
30. Given an ellipse x 2ya 2 1 y 2yb 2 − 1, where a ± b, find the equation of the set of all points
from which there are two tangents to the curve whose slopes are (a) reciprocals and
(b) negative reciprocals.
31. Find the two points on the curve y − x 4 2 2x 2 2 x that have a common tangent line.
32. Suppose that three points on the parabola y − x 2 have the property that their normal lines
intersect at a common point. Show that the sum of their x-coordinates is 0.
33. A lattice point in the plane is a point with integer coordinates. Suppose that circles with
radius r are drawn using all lattice points as centers. Find the smallest value of r such that
any line with slope 25 intersects some of these circles.
34. A cone of radius r centimeters and height h centimeters is lowered point first at a rate of
1 cmys into a tall cylinder of radius R centimeters that is partially filled with water. How fast
is the water level rising at the instant the cone is completely submerged?
35. A container in the shape of an inverted cone has height 16 cm and radius 5 cm at the top. It
is partially filled with a liquid that oozes through the sides at a rate proportional to the area
of the container that is in contact with the liquid. (The surface area of a cone is !rl, where
r is the radius and l is the slant height.) If we pour the liquid into the container at a rate of
2 cm3ymin, then the height of the liquid decreases at a rate of 0.3 cmymin when the height
is 10 cm. If our goal is to keep the liquid at a constant height of 10 cm, at what rate should
we pour the liquid into the container?
278
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The great mathematician Leonard Euler observed “… nothing at all takes place in the universe in which some rule of maximum or
minimum does not appear.” In Exercise 4.7.53 you will use calculus to show that bees construct the cells in their hive in a shape that
minimizes surface area.
Kostiantyn Kravchenko / Shutterstock.com
4
Applications of Differentiation
WE HAVE ALREADY INVESTIGATED SOME of the applications of derivatives, but now that we
know the differentiation rules we are in a better position to pursue the applications of differentiation in greater depth. Here we learn what derivatives tell us about the shape of a graph of a function and, in particular, how they help us locate maximum and minimum values of functions. Many
practical problems require us to minimize a cost or maximize an area or somehow find the best
possible outcome of a situation. In particular, we will be able to investigate the optimal shape of a
can and to explain the location of rainbows in the sky.
279
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280
CHAPTER 4
Applications of Differentiation
4.1 Maximum and Minimum Values
Some of the most important applications of differential calculus are optimization problems, in which we are required to find the optimal (best) way of doing something. Here
are examples of such problems that we will solve in this chapter:
What is the shape of a can that minimizes manufacturing costs?
● What is the maximum acceleration of a spacecraft? (This is an important question for
the astronauts who have to withstand the effects of acceleration.)
● What is the radius of a contracted windpipe that expels air most rapidly during a cough?
● At what angle should blood vessels branch so as to minimize the energy expended
by the heart in pumping blood?
●
These problems can be reduced to finding the maximum or minimum values of a function. Let’s first explain exactly what we mean by maximum and minimum values.
■ Absolute and Local Extreme Values
y
We see that the highest point on the graph of the function f shown in Figure 1 is the point
s3, 5d. In other words, the largest value of f is f s3d − 5. Likewise, the smallest value is
f s6d − 2. We say that f s3d − 5 is the absolute maximum of f and f s6d − 2 is the absolute minimum. In general, we use the following definition.
4
2
0
2
4
x
6
1 Definition Let c be a number in the domain D of a function f. Then f scd is the
● absolute maximum value of f on D if f scd > f sxd for all x in D.
● absolute minimum value of f on D if f scd < f sxd for all x in D.
FIGURE 1
y
f(d)
f(a)
a
0
b
c
d
e
x
FIGURE 2
Abs min f sad, abs max f sd d,
loc min f scd, f sed, loc max f sbd, f sd d
An absolute maximum or minimum is sometimes called a global maximum or minimum. The maximum and minimum values of f are called extreme values of f.
Figure 2 shows the graph of a function f with absolute maximum at d and absolute
minimum at a. Note that sd, f sddd is the highest point on the graph and sa, f sadd is the
lowest point. In Figure 2, if we consider only values of x near b [for instance, if we
restrict our attention to the interval sa, cd], then f sbd is the largest of those values of f sxd
and is called a local maximum value of f. Likewise, f scd is called a local minimum value
of f because f scd < f sxd for x near c [in the interval sb, dd, for instance]. The function f
also has a local minimum at e. In general, we have the following definition.
2 Definition The number f scd is a
● local maximum value of f if f scd > f sxd when x is near c.
● local minimum value of f if f scd < f sxd when x is near c.
y
loc
max
loc
and
abs
min
I
J
K
4
8
12
6
4
loc
min
2
0
FIGURE 3
x
In Definition 2 (and elsewhere), if we say that something is true near c, we mean that
it is true on some open interval containing c. (Thus a local maximum or minimum can’t
occur at an endpoint.) For instance, in Figure 3 we see that f s4d − 5 is a local minimum
because it’s the smallest value of f on the interval I. It’s not the absolute minimum
because f sxd takes on smaller values when x is near 12 (in the interval K, for instance).
In fact f s12d − 3 is both a local minimum and the absolute minimum. Similarly,
f s8d − 7 is a local maximum, but not the absolute maximum because f takes on larger
values near 1.
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SECTION 4.1
y
281
Maximum and Minimum Values
EXAMPLE 1 The graph of the function
(_1, 37)
y=3x$-16˛+18≈
f sxd − 3x 4 2 16x 3 1 18x 2
(1, 5)
_1
1
2
3
4
5
x
(3, _27)
is shown in Figure 4. You can see that f s1d − 5 is a local maximum, whereas the
absolute maximum is f s21d − 37. (This absolute maximum is not a local maximum
because it occurs at an endpoint.) Also, f s0d − 0 is a local minimum and f s3d − 227
is both a local and an absolute minimum. Note that f has neither a local nor an absolute
maximum at x − 4.
n
EXAMPLE 2 The function f sxd − cos x takes on its (local and absolute) maximum value of 1 infinitely many times, because cos 2n! − 1 for any integer n and
21 < cos x < 1 for all x. (See Figure 5.) Likewise, coss2n 1 1d! − 21 is its
minimum value, where n is any integer.
FIGURE 4
y
Local and absolute maximum
0
π
FIGURE 5
x
n
f s0d − 0 is the absolute (and local) minimum value of f . This corresponds to the fact
that the origin is the lowest point on the parabola y − x 2. (See Figure 6.) However,
there is no highest point on the parabola and so this function has no maximum value. n
x
EXAMPLE 4 From the graph of the function f sxd − x 3, shown in Figure 7, we see that
FIGURE 6
Mimimum value 0, no maximum
y
this function has neither an absolute maximum value nor an absolute minimum value.
In fact, it has no local extreme values either.
n
We have seen that some functions have extreme values, whereas others do not. The
following theorem gives conditions under which a function is guaranteed to possess
extreme values.
y=˛
0
3π
EXAMPLE 3 If f sxd − x 2, then f sxd > f s0d because x 2 > 0 for all x. Therefore
y=≈
0
2π
Local and absolute minimum
y − cos x
y
21 < x < 4
x
3 The Extreme Value Theorem If f is continuous on a closed interval fa, bg,
then f attains an absolute maximum value f scd and an absolute minimum value
f sdd at some numbers c and d in fa, bg.
FIGURE 7
No mimimum, no maximum
The Extreme Value Theorem is illustrated in Figure 8. Note that an extreme value can
be taken on more than once. Although the Extreme Value Theorem is intuitively very
plausible, it is difficult to prove and so we omit the proof.
y
y
y
FIGURE 8
Functions continuous on a closed
interval always attain extreme values.
0
a
c
d b
x
0
a
c
d=b
x
0
a c¡
d
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c™ b
x
282
CHAPTER 4
Applications of Differentiation
Figures 9 and 10 show that a function need not possess extreme values if either
hypothesis (continuity or closed interval) is omitted from the Extreme Value Theorem.
y
y
3
g
f
1
0
1
2
x
FIGURE 9
This function has minimum value
f(2)=0, but no maximum value.
0
2
x
FIGURE 10
This continuous function g has
no maximum or minimum.
The function f whose graph is shown in Figure 9 is defined on the closed interval
[0, 2] but has no maximum value. (Notice that the range of f is [0, 3d. The function takes
on values arbitrarily close to 3, but never actually attains the value 3.) This does not contradict the Extreme Value Theorem because f is not continuous. [Nonetheless, a discontinuous function could have maximum and minimum values. See Exercise 13(b).]
The function t shown in Figure 10 is continuous on the open interval s0, 2d but has
neither a maximum nor a minimum value. [The range of t is s1, `d. The function takes
on arbitrarily large values.] This does not contradict the Extreme Value Theorem because
the interval s0, 2d is not closed.
■ Critical Numbers and the Closed Interval Method
y
The Extreme Value Theorem says that a continuous function on a closed interval has a
maximum value and a minimum value, but it does not tell us how to find these extreme
values. Notice in Figure 8 that the absolute maximum and minimum values that are
between a and b occur at local maximum or minimum values, so we start by looking for
local extreme values.
Figure 11 shows the graph of a function f with a local maximum at c and a local
minimum at d. It appears that at the maximum and minimum points the tangent lines are
horizontal and therefore each has slope 0. We know that the derivative is the slope of the
tangent line, so it appears that f 9scd − 0 and f 9sdd − 0. The following theorem says that
this is always true for differentiable functions.
{c, f(c)}
{d, f(d )}
0
c
FIGURE 11
d
x
4 Fermat’s Theorem If f has a local maximum or minimum at c, and if f 9scd
exists, then f 9scd − 0.
PROOF Suppose, for the sake of definiteness, that f has a local maximum at c. Then,
according to Definition 2, f scd > f sxd if x is sufficiently close to c. This implies that if
h is sufficiently close to 0, with h being positive or negative, then
f scd > f sc 1 hd
and therefore
5
f sc 1 hd 2 f scd < 0
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SECTION 4.1
Fermat
Fermat’s Theorem is named after
Pierre Fermat (1601–1665), a French
lawyer who took up mathematics as
a hobby. Despite his amateur status,
Fermat was one of the two inventors
of analytic geometry (Descartes was
the other). His methods for finding
tangents to curves and maximum
and minimum values (before the
invention of limits and derivatives)
made him a forerunner of Newton in
the creation of differential calculus.
Maximum and Minimum Values
283
We can divide both sides of an inequality by a positive number. Thus, if h . 0 and h is
sufficiently small, we have
f sc 1 hd 2 f scd
<0
h
Taking the right-hand limit of both sides of this inequality (using Theorem 2.3.2), we get
lim1
hl 0
f sc 1 hd 2 f scd
< lim1 0 − 0
h l0
h
But since f 9scd exists, we have
f sc 1 hd 2 f scd
f sc 1 hd 2 f scd
− lim1
hl0
h l0
h
h
f 9scd − lim
and so we have shown that f 9scd < 0.
If h , 0, then the direction of the inequality (5) is reversed when we divide by h:
f sc 1 hd 2 f scd
>0
h
So, taking the left-hand limit, we have
f sc 1 hd 2 f scd
f sc 1 hd 2 f scd
− lim2
>0
hl0
h l0
h
h
f 9scd − lim
We have shown that f 9scd > 0 and also that f 9scd < 0. Since both of these inequalities
must be true, the only possibility is that f 9scd − 0.
We have proved Fermat’s Theorem for the case of a local maximum. The case of a
local minimum can be proved in a similar manner, or see Exercise 81 for an alternate
method.
n
The following examples caution us against reading too much into Fermat’s Theorem:
we can’t expect to locate extreme values simply by setting f 9sxd − 0 and solving for x.
y
y=˛
EXAMPLE 5 If f sxd − x 3, then f 9sxd − 3x 2, so f 9s0d − 0. But f has no maximum or
0
x
FIGURE 12
If f sxd − x 3, then f 9s0d − 0, but
f has no maximum or minimum.
y
y=|x|
0
FIGURE 13
| |
x
If f sxd − x , then f s0d − 0 is a minimum value, but f 9s0d does not exist.
minimum at 0, as you can see from its graph in Figure 12. (Or observe that x 3 . 0 for
x . 0 but x 3 , 0 for x , 0.) The fact that f 9s0d − 0 simply means that the curve
y − x 3 has a horizontal tangent at s0, 0d. Instead of having a maximum or minimum at
s0, 0d, the curve crosses its horizontal tangent there.
n
| |
EXAMPLE 6 The function f sxd − x has its (local and absolute) minimum value
at 0, but that value can’t be found by setting f 9sxd − 0 because, as was shown in
Example 2.8.5, f 9s0d does not exist. (See Figure 13.)
n
WARNING Examples 5 and 6 show that we must be careful when using Fermat’s
Theorem. Example 5 demonstrates that even when f 9scd − 0 there need not be a maximum or minimum at c. (In other words, the converse of Fermat’s Theorem is false in
general.) Furthermore, there may be an extreme value even when f 9scd does not exist
(as in Example 6).
Fermat’s Theorem does suggest that we should at least start looking for extreme values of f at the numbers c where f 9scd − 0 or where f 9scd does not exist. Such numbers
are given a special name.
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284
CHAPTER 4
Applications of Differentiation
6 Definition A critical number of a function f is a number c in the domain of
f such that either f 9scd − 0 or f 9scd does not exist.
EXAMPLE 7 Find the critical numbers of (a) f sxd − x 3 2 3x 2 1 1 and
(b) f sxd − x 3y5s4 2 xd.
SOLUTION
(a) The derivative of f is f 9sxd − 3x 2 2 6x − 3xsx 2 2d. Since f 9sxd exists for all x,
the only critical numbers of f occur when f 9sxd − 0, that is, when x − 0 or x − 2.
(b) First note that the domain of f is R. The Product Rule gives
Figure 14 shows a graph of the
function f in Example 7(b). It supports our answer because there is a
horizontal tangent when x − 1.5
fwhere f 9sxd − 0g and a vertical
tangent when x − 0 fwhere f 9sxd
is undefinedg.
f 9sxd − x 3y5s21d 1 s4 2 xd(53 x22y5) − 2x 3y5 1
−
3.5
3s4 2 xd
5x 2 y5
25x 1 3s4 2 xd
12 2 8x
−
2y5
5x
5x 2y5
[The same result could be obtained by first writing f sxd − 4x 3y5 2 x 8y5.] Therefore
f 9sxd − 0 if 12 2 8x − 0, that is, x − 32, and f 9sxd does not exist when x − 0. Thus the
critical numbers are 32 and 0.
n
5
_0.5
In terms of critical numbers, Fermat’s Theorem can be rephrased as follows (compare
Definition 6 with Theorem 4):
_2
FIGURE 14
7 If f has a local maximum or minimum at c, then c is a critical number of f.
To find an absolute maximum or minimum of a continuous function on a closed interval, we note that either it is local [in which case it occurs at a critical number by (7)] or
it occurs at an endpoint of the interval, as we see from the examples in Figure 8. Thus the
following three-step procedure always works.
The Closed Interval Method To find the absolute maximum and minimum
values of a continuous function f on a closed interval fa, bg:
1. Find the values of f at the critical numbers of f in sa, bd.
2. Find the values of f at the endpoints of the interval.
3. The largest of the values from Steps 1 and 2 is the absolute maximum value;
the smallest of these values is the absolute minimum value.
EXAMPLE 8 Find the absolute maximum and minimum values of the function
212 < x < 4
f sxd − x 3 2 3x 2 1 1
f
g
SOLUTION Since f is continuous on 212, 4 , we can use the Closed Interval Method.
In Example 7(a) we found the critical numbers x − 0 and x − 2. Notice that each of
these critical numbers lies in the interval (212 , 4). The values of f at these critical
numbers are
f s0d − 1
f s2d − 23
The values of f at the endpoints of the interval are
f (212 ) − 18
f s4d − 17
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SECTION 4.1
y
20
y=˛-3≈+1
(4, 17)
15
10
5
_1 0
_5
1
3
EXAMPLE 9
(a) Use a calculator or computer to estimate the absolute minimum and maximum
values of the function f sxd − x 2 2 sin x, 0 < x < 2!.
(b) Use calculus to find the exact minimum and maximum values.
8
_1
Comparing these four numbers, we see that the absolute maximum value is f s4d − 17
and the absolute minimum value is f s2d − 23.
In this example the absolute maximum occurs at an endpoint, whereas the absolute
minimum occurs at a critical number. The graph of f is sketched in Figure 15.
n
x
4
FIGURE 15
0
285
With graphing software or a graphing calculator it is possible to estimate maximum
and minimum values very easily. But, as the next example shows, calculus is needed to
find the exact values.
2
(2, _3)
Maximum and Minimum Values
2π
SOLUTION
(a) Figure 16 shows a graph of f in the viewing rectangle f0, 2!g by f21, 8g. The
absolute maximum value is about 6.97 and it occurs when x < 5.24. Similarly, the
absolute minimum value is about 20.68 and it occurs when x < 1.05. It is possible
to get more accurate numerical estimates, but for exact values we must use calculus.
(b) The function f sxd − x 2 2 sin x is continuous on f0, 2!g. Since
f 9sxd − 1 2 2 cos x, we have f 9sxd − 0 when cos x − 12 and this occurs when
x − !y3 or 5!y3. The values of f at these critical numbers are
FIGURE 16
and
f s!y3d −
!
!
!
2 2 sin
−
2 s3 < 20.684853
3
3
3
f s5!y3d −
5!
5!
5!
2 2 sin
−
1 s3 < 6.968039
3
3
3
The values of f at the endpoints are
f s0d − 0
f s2!d − 2! < 6.28
Comparing these four numbers and using the Closed Interval Method, we see that the
absolute minimum value is f s!y3d − !y3 2 s3 and the absolute maximum value is
f s5!y3d − 5!y3 1 s3 . The values from part (a) serve as a check on our work.
n
EXAMPLE 10 The Hubble Space Telescope was deployed on April 24, 1990, by the
space shuttle Discovery. A model for the velocity of the shuttle during this mission,
from liftoff at t − 0 until the solid rocket boosters were jettisoned at t − 126 seconds,
is given by
vstd − 0.001302t 3 2 0.09029t 2 1 23.61t 2 3.083
NASA
(in feet per second). Using this model, estimate the absolute maximum and minimum
values of the acceleration of the shuttle between liftoff and the jettisoning of the boosters.
SOLUTION We are asked for the extreme values not of the given velocity function,
but rather of the acceleration function. So we first need to differentiate to find the
acceleration:
astd − v9std −
d
s0.001302t 3 2 0.09029t 2 1 23.61t 2 3.083d
dt
− 0.003906t 2 2 0.18058t 1 23.61
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286
CHAPTER 4
Applications of Differentiation
We now apply the Closed Interval Method to the continuous function a on the interval
0 < t < 126. Its derivative is
a9std − 0.007812t 2 0.18058
The only critical number occurs when a9std − 0:
t1 −
0.18058
< 23.12
0.007812
Evaluating astd at the critical number and at the endpoints, we have
ast1 d < 21.52
as0d − 23.61
as126d < 62.87
So the maximum acceleration is about 62.87 ftys2 and the minimum acceleration is
about 21.52 ftys2.
4.1
n
Exercises
1. Explain the difference between an absolute minimum and
a local minimum.
5–6 Use the graph to state the absolute and local maximum and
minimum values of the function.
2. Suppose f is a continuous function defined on a closed
interval fa, bg.
(a) What theorem guarantees the existence of an absolute maximum value and an absolute minimum value
for f ?
(b) What steps would you take to find those maximum
and minimum values?
5.
3–4 For each of the numbers a, b, c, d, r, and s, state whether the
function whose graph is shown has an absolute maximum or minimum, a local maximum or minimum, or neither a maximum nor
a minimum.
3.
6.
y
y
y=©
y=ƒ
1
0
1
1
x
0
1
x
7–10 Sketch the graph of a function f that is continuous on [1, 5]
and has the given properties.
7. Absolute maximum at 5, absolute minimum at 2,
local maximum at 3, local minima at 2 and 4
y
8. Absolute maximum at 4, absolute minimum at 5,
local maximum at 2, local minimum at 3
0 a
b
c
d
r
s
x
10. Absolute maximum at 2, absolute minimum at 5,
4 is a critical number but there is no local maximum
or minimum there.
4. y
0
9. Absolute minimum at 3, absolute maximum at 4,
local maximum at 2
a
b
c
d
r
s
x
11. (a) Sketch the graph of a function that has a local maximum
at 2 and is differentiable at 2.
(b) Sketch the graph of a function that has a local maximum
at 2 and is continuous but not differentiable at 2.
(c) Sketch the graph of a function that has a local maximum
at 2 and is not continuous at 2.
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SECTION 4.1
12. (a) Sketch the graph of a function on [21, 2] that has an
absolute maximum but no local maximum.
(b) Sketch the graph of a function on [21, 2] that has a local
maximum but no absolute maximum.
13. (a) Sketch the graph of a function on [21, 2] that has an
absolute maximum but no absolute minimum.
(b) Sketch the graph of a function on [21, 2] that is
discontinuous but has both an absolute maximum and
an absolute minimum.
14. (a) Sketch the graph of a function that has two local maxima, one local minimum, and no absolute minimum.
(b) Sketch the graph of a function that has three local
minima, two local maxima, and seven critical numbers.
15–28 Sketch the graph of f by hand and use your sketch to
find the absolute and local maximum and minimum values of f.
(Use the graphs and transformations of Sections 1.2 and 1.3.)
15. f sxd − 3 2 2x,
x > 21
16. f sxd − x , 21 < x , 2
x>1
18. f sxd − 1yx,
1,x,3
; 49–50 A formula for the derivative of a function f is given. How
many critical numbers does f have?
49. f 9sxd − 5e20.1 | x | sin x 2 1
50. f 9sxd −
100 cos 2 x
21
10 1 x 2
51–66 Find the absolute maximum and absolute minimum values
of f on the given interval.
51. f sxd − 12 1 4x 2 x 2,
f0, 5g
52. f sxd − 5 1 54x 2 2x ,
3
f0, 4g
53. f sxd − 2x 2 3x 2 12x 1 1,
3
2
f22, 3g
54. f sxd − x 2 6x 1 5, f23, 5g
3
2
f22, 3g
f22, 3g
3
1
, f0.2, 4g
x
x
58. f sxd − 2
, f0, 3g
x 2x11
3
59. f std − t 2 s
t,
60. f sxd −
23!y2 < t < 3!y2
H
H
48. Bsud − 4 tan21u 2 u
57. f sxd − x 1
21. f sxd − sin x, 2!y2 < x < !y2
25. f sxd − 1 2 sx
47. tsxd − x 2 ln x
56. f std − st 2 4d ,
20. f sxd − sin x, 0 , x < !y2
23. f sxd − ln x, 0 , x < 2
46. pstd − te 4t
2
19. f sxd − sin x, 0 < x , !y2
22. f std − cos t,
287
45. f s"d − 2 cos " 1 sin2 "
55. f sxd − 3x 4 2 4x 3 2 12x 2 1 1,
2
17. f sxd − 1yx,
Maximum and Minimum Values
f21, 4g
x
e
, [0, 3]
1 1 x2
61. f std − 2 cos t 1 sin 2t,
| |
24. f sxd − x
f0, !y2g
62. f s"d − 1 1 cos ", [!y4, !]
2
26. f sxd − e x
63. f sxd − x22 ln x,
x2
if 21 < x < 0
27. f sxd −
2 2 3x if 0 , x < 1
f 12 , 4g
64. f sxd − xe xy2, f23, 1g
65. f sxd − lnsx 2 1 x 1 1d, f21, 1g
2x 1 1 if 0 < x , 1
28. f sxd −
4 2 2x if 1 < x < 3
66. f sxd − x 2 2 tan21 x,
29–48 Find the critical numbers of the function.
2
29. f sxd − 3x 1 x 2 2
30. tsvd − v 2 12v 1 4
31. f sxd − 3x 4 1 8x 3 2 48x 2
32. f sxd − 2x 3 1 x 2 1 8x
33. tstd − t 5 1 5t 3 1 50t
34. Asxd − 3 2 2x
3
|
35. tsyd −
y21
y2 2 y 1 1
36. hs pd −
p21
p2 1 4
37. psxd −
x2 1 2
2x 2 1
38. qstd −
t2 1 9
t2 2 9
|
39. hstd − t 3y4 2 2 t 1y4
3
40. tsxd − s
4 2 x2
41. Fsxd − x 4y5sx 2 4d 2
42. hsxd − x21y3sx 2 2d
43. f sxd − x 1y3s4 2 xd2y3
44. f s"d − " 1 s2 cos "
f0, 4g
67. If a and b are positive numbers, find the maximum value
of f sxd − x as1 2 xd b, 0 < x < 1.
; 68. Use a graph to estimate the critical numbers of
f sxd − 1 1 5x 2 x 3 correct to one decimal place.
|
|
; 69–72
(a) Use a graph to estimate the absolute maximum and minimum
values of the function to two decimal places.
(b) Use calculus to find the exact maximum and minimum values.
69. f sxd − x 5 2 x 3 1 2, 21 < x < 1
70. f sxd − e x 1 e 22x, 0 < x < 1
71. f sxd − x sx 2 x 2
72. f sxd − x 2 2 cos x, 22 < x < 0
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288
CHAPTER 4
Applications of Differentiation
73. After an alcoholic beverage is consumed, the concentration of
alcohol in the bloodstream (blood alcohol concentration, or
BAC) surges as the alcohol is absorbed, followed by a gradual decline as the alcohol is metabolized. The function
Cstd − 0.135te22.802t
models the average BAC, measured in gydL, of a group of
eight male subjects t hours after rapid consumption of
15 mL of ethanol (corresponding to one alcoholic drink).
What is the maximum average BAC during the first
3 hours? When does it occur?
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of Ethanol after
Oral Administration in the Fasting State,” Journal of Pharmacokinetics and
Biopharmaceutics 5 (1977): 207–24.
74. After an antibiotic tablet is taken, the concentration of the
antibiotic in the bloodstream is modeled by the function
Cstd − 8se20.4t 2 e20.6t d
where the time t is measured in hours and C is measured in
!gymL. What is the maximum concentration of the antibiotic during the first 12 hours?
75. Between 0°C and 30°C, the volume V (in cubic centimeters)
of 1 kg of water at a temperature T is given approximately
by the formula
V − 999.87 2 0.06426T 1 0.0085043T 2 2 0.0000679T 3
Find the temperature at which water has its maximum density.
76. An object with weight W is dragged along a horizontal
plane by a force acting along a rope attached to the object.
If the rope makes an angle " with the plane, then the magnitude of the force is
F−
#W
# sin " 1 cos "
where # is a positive constant called the coefficient of
friction and where 0 < " < !y2. Show that F is minimized
when tan " − #.
77. The water level, measured in feet above mean sea level, of
Lake Lanier in Georgia, USA, during 2012 can be modeled
by the function
Lstd − 0.01441t 3 2 0.4177t 2 1 2.703t 1 1060.1
where t is measured in months since January 1, 2012. Estimate when the water level was highest during 2012.
78. In 1992 the space shuttle Endeavour was launched on mission STS-49 in order to install a new perigee kick motor in
an Intelsat communications satellite. The table gives the
velocity data for the shuttle between liftoff and the jettisoning of the solid rocket boosters.
(a) Use a graphing calculator or computer to find the
cubic polynomial that best models the velocity of the
shuttle for the time interval t [ f0, 125g. Then graph
this polynomial.
(b) Find a model for the acceleration of the shuttle and
use it to estimate the maximum and minimum values of
the acceleration during the first 125 seconds.
Event
Time (s) Velocity (ftys)
Launch
Begin roll maneuver
End roll maneuver
Throttle to 89%
Throttle to 67%
Throttle to 104%
Maximum dynamic pressure
Solid rocket booster separation
0
10
15
20
32
59
62
125
0
185
319
447
742
1325
1445
4151
79. When a foreign object lodged in the trachea forces a person to
cough, the diaphragm thrusts upward, causing an increase in
pressure in the lungs. This is accompanied by a contraction of
the trachea, making a narrower channel for the expelled air to
flow through. For a given amount of air to escape in a fixed
time, it must move faster through the narrower channel than
the wider one. The greater the velocity of the airstream, the
greater the force on the foreign object. X-rays show that the
radius of the circular tracheal tube contracts to about twothirds of its normal radius during a cough. According to a
mathematical model of coughing, the velocity v of the airstream is related to the radius r of the trachea by the equation
vsrd − ksr0 2 rdr 2
1
2 r0 < r < r0
where k is a constant and r0 is the normal radius of the trachea. The restriction on r is due to the fact that the tracheal
wall stiffens under pressure and a contraction greater than
1
2 r0 is prevented (otherwise the person would suffocate).
f
g
(a) Determine the value of r in the interval 12 r 0 , r 0 at
which v has an absolute maximum. How does this
compare with experimental evidence?
(b) What is the absolute maximum value of v on the interval?
(c) Sketch the graph of v on the interval f0, r0 g.
80. Prove that the function
f sxd − x 101 1 x 51 1 x 1 1
has neither a local maximum nor a local minimum.
81. (a) If f has a local minimum value at c, show that the function tsxd − 2f sxd has a local maximum value at c.
(b) Use part (a) to prove Fermat’s Theorem for the case in
which f has a local minimum at c.
82. A cubic function is a polynomial of degree 3; that is, it has
the form f sxd − ax 3 1 bx 2 1 cx 1 d, where a ± 0.
(a) Show that a cubic function can have two, one, or no
critical number(s). Give examples and sketches to
illustrate the three possibilities.
(b) How many local extreme values can a cubic function
have?
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APPLIED PROJECT
APPLIED PROJECT
The Calculus of Rainbows
289
THE CALCULUS OF RAINBOWS
Rainbows are created when raindrops scatter sunlight. They have fascinated mankind since
ancient times and have inspired attempts at scientific explanation since the time of Aristotle.
In this project we use the ideas of Descartes and Newton to explain the shape, location, and
colors of rainbows.
å A
from
sun
∫
∫
O
B
D(å )
∫
∫
C
å
to
observer
Formation of the primary rainbow
1. The figure shows a ray of sunlight entering a spherical raindrop at A. Some of the light
is reflected, but the line AB shows the path of the part that enters the drop. Notice that
the light is refracted toward the normal line AO and in fact Snell’s Law says that
sin $ − k sin %, where $ is the angle of incidence, % is the angle of refraction, and k < 43
is the index of refraction for water. At B some of the light passes through the drop and is
refracted into the air, but the line BC shows the part that is reflected. (The angle of incidence equals the angle of reflection.) When the ray reaches C, part of it is reflected, but for
the time being we are more interested in the part that leaves the raindrop at C. (Notice that
it is refracted away from the normal line.) The angle of deviation Ds$d is the amount of
clockwise rotation that the ray has undergone during this three-stage process. Thus
Ds$d − s$ 2 %d 1 s! 2 2%d 1 s$ 2 %d − ! 1 2$ 2 4%
Show that the minimum value of the deviation is Ds$d < 1388 and occurs when
$ < 59.48.
The significance of the minimum deviation is that when $ < 59.48 we have D9s$d < 0,
so DDyD$ < 0. This means that many rays with $ < 59.48 become deviated by approximately the same amount. It is the concentration of rays coming from near the direction of
minimum deviation that creates the brightness of the primary rainbow. The figure at the
left shows that the angle of elevation from the observer up to the highest point on the rainbow is 180 8 2 1388 − 428. (This angle is called the rainbow angle.)
rays from sun
138°
rays from sun
42°
2. Problem 1 explains the location of the primary rainbow, but how do we explain the colors? Sunlight comprises a range of wavelengths, from the red range through orange, yellow, green, blue, indigo, and violet. As Newton discovered in his prism experiments of
1666, the index of refraction is different for each color. (The effect is called dispersion.)
For red light the refractive index is k < 1.3318, whereas for violet light it is k < 1.3435.
By repeating the calculation of Problem 1 for these values of k, show that the rainbow
angle is about 42.38 for the red bow and 40.68 for the violet bow. So the rainbow really
consists of seven individual bows corresponding to the seven colors.
observer
3. Perhaps you have seen a fainter secondary rainbow above the primary bow. That results
from the part of a ray that enters a raindrop and is refracted at A, reflected twice (at B and
C), and refracted as it leaves the drop at D (see the figure at the left). This time the deviation angle Ds$d is the total amount of counterclockwise rotation that the ray undergoes in
this four-stage process. Show that
C
å
∫
D
∫
∫
to
observer
from
sun
å
∫
∫
∫
A
Formation of the secondary rainbow
Ds$d − 2$ 2 6% 1 2!
B
and Dsad has a minimum value when
cos $ −
Î
k2 2 1
8
(continued )
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290
CHAPTER 4
Applications of Differentiation
Taking k − 43, show that the minimum deviation is about 1298 and so the rainbow angle for
the secondary rainbow is about 518, as shown in the figure at the left.
Leonid Andronov / Shutterstock.com
4. Show that the colors in the secondary rainbow appear in the opposite order from those in
the primary rainbow.
42° 51°
4.2 The Mean Value Theorem
We will see that many of the results of this chapter depend on one central fact, which is
called the Mean Value Theorem.
■ Rolle’s Theorem
To arrive at the Mean Value Theorem, we first need the following result.
Rolle
Rolle’s Theorem Let f be a function that satisfies the following three hypotheses:
1. f is continuous on the closed interval fa, bg.
2. f is differentiable on the open interval sa, bd.
3. f sad − f sbd
Rolle’s Theorem was first published in
1691 by the French mathematician
Michel Rolle (1652–1719) in a book
entitled Méthode pour resoudre les
egalitez. He was a vocal critic of the
methods of his day and attacked calculus as being a “collection of ingenious
fallacies.” Later, however, he became
convinced of the essential correctness
of the methods of calculus.
y
0
Then there is a number c in sa, bd such that f 9scd − 0.
Before giving the proof let’s take a look at the graphs of some typical functions that
satisfy the three hypotheses. Figure 1 shows the graphs of four such functions. In each
case it appears that there is at least one point sc, f scdd on the graph where the tangent is
horizontal and therefore f 9scd − 0. Thus Rolle’s Theorem is plausible.
y
a
c¡
(a)
c™ b
x
0
y
a
c
(b)
b
x
0
y
a
c¡
(c)
c™
b
x
0
a
c
b
x
(d)
FIGURE 1
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SECTION 4.2
The Mean Value Theorem
291
PROOF There are three cases:
PS
CASE I f sxd − k, a constant
Take cases
Then f 9sxd − 0, so the number c can be taken to be any number in sa, bd.
CASE II f sxd . f sad for some x in sa, bd [as in Figure 1(b) or (c)]
By the Extreme Value Theorem (which we can apply by hypothesis 1), f has a maximum value somewhere in fa, bg. Since f sad − f sbd, it must attain this maximum value
at a number c in the open interval sa, bd. Then f has a local maximum at c and, by
hypothesis 2, f is differentiable at c. Therefore f 9scd − 0 by Fermat’s Theorem.
CASE III f sxd , f sad for some x in sa, bd [as in Figure 1(c) or (d)]
By the Extreme Value Theorem, f has a minimum value in fa, bg and, since
f sad − f sbd, it attains this minimum value at a number c in sa, bd. Again f 9scd − 0 by
Fermat’s Theorem.
n
EXAMPLE 1 Let’s apply Rolle’s Theorem to the position function s − f std of a
moving object. If the object is in the same place at two different instants t − a and
t − b, then f sad − f sbd. Rolle’s Theorem says that there is some instant of time t − c
between a and b when f 9scd − 0; that is, the velocity is 0. (In particular, you can see
that this is true when a ball is thrown directly upward.)
n
Figure 2 shows a graph of the function f sxd − x 3 1 x 2 1 discussed in
Example 2. Rolle’s Theorem shows
that, no matter how much we enlarge
the viewing rectangle, we can never
find a second x-intercept.
3
_2
2
EXAMPLE 2 Prove that the equation x 3 1 x 2 1 − 0 has exactly one real solution.
SOLUTION First we use the Intermediate Value Theorem (2.5.10) to show that a
solution exists. Let f sxd − x 3 1 x 2 1. Then f s0d − 21 , 0 and f s1d − 1 . 0.
Since f is a polynomial, it is continuous, so the Intermediate Value Theorem states
that there is a number c between 0 and 1 such that f scd − 0. Thus the given equation
has a solution.
To show that the equation has no other real solution, we use Rolle’s Theorem and
argue by contradiction. Suppose that it had two solutions a and b. Then f sad − 0 − f sbd
and, since f is a polynomial, it is differentiable on sa, bd and continuous on fa, bg. Thus,
by Rolle’s Theorem, there is a number c between a and b such that f 9scd − 0. But
f 9sxd − 3x 2 1 1 > 1
for all x
2
_3
FIGURE 2
(since x > 0) so f 9sxd can never be 0. This gives a contradiction. Therefore the
equation can’t have two real solutions.
n
■ The Mean Value Theorem
Our main use of Rolle’s Theorem is in proving the following important theorem, which
was first stated by another French mathematician, Joseph-Louis Lagrange.
The Mean Value Theorem is an
example of what is called an existence
theorem. Like the Intermediate Value
Theorem, the Extreme Value Theorem, and Rolle’s Theorem, it guarantees that there exists a number with a
certain property, but it doesn’t tell us
how to find the number.
The Mean Value Theorem Let f be a function that satisfies the following
hypotheses:
1. f is continuous on the closed interval fa, bg.
2. f is differentiable on the open interval sa, bd.
Then there is a number c in sa, bd such that
1
f 9scd −
f sbd 2 f sad
b2a
or, equivalently,
2
f sbd 2 f sad − f 9scdsb 2 ad
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292
CHAPTER 4
Applications of Differentiation
Before proving this theorem, we can see that it is reasonable by interpreting it geometrically. Figures 3 and 4 show the points Asa, f sadd and Bsb, f sbdd on the graphs of two
differentiable functions. The slope of the secant line AB is
3
mAB −
f sbd 2 f sad
b2a
which is the same expression as on the right side of Equation 1. Since f 9scd is the slope of
the tangent line at the point sc, f scdd, the Mean Value Theorem, in the form given by Equation 1, says that there is at least one point Psc, f scdd on the graph where the slope of the
tangent line is the same as the slope of the secant line AB. In other words, there is a point
P where the tangent line is parallel to the secant line AB. (Imagine a line far away that
stays parallel to AB while moving toward AB until it touches the graph for the first time.)
y
y
P { c, f(c)}
P¡
B
P™
A
A{ a, f(a)}
B { b, f(b)}
0
a
c
b
x
0
FIGURE 3
y
h(x)
A
ƒ
0
b
f(b)-f(a)
f(a)+
(x-a)
b-a
FIGURE 5
x
c¡
c™
b
x
FIGURE 4
PROOF We apply Rolle’s Theorem to a new function h defined as the difference
between f and the function whose graph is the secant line AB. Using Equation 3
and the point-slope equation of a line, we see that the equation of the line AB can
be written as
B
x
a
y=ƒ
a
or as
y 2 f sad −
f sbd 2 f sad
sx 2 ad
b2a
y − f sad 1
f sbd 2 f sad
sx 2 ad
b2a
So, as shown in Figure 5,
4
hsxd − f sxd 2 f sad 2
f sbd 2 f sad
sx 2 ad
b2a
First we must verify that h satisfies the three hypotheses of Rolle’s Theorem.
1. The function h is continuous on fa, bg because it is the sum of f and a firstdegree polynomial, both of which are continuous.
2. The function h is differentiable on sa, bd because both f and the first-degree
polynomial are differentiable. In fact, we can compute h9 directly from Equation 4:
h9sxd − f 9sxd 2
f sbd 2 f sad
b2a
(Note that f sad and f f sbd 2 f sadgysb 2 ad are constants.)
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SECTION 4.2
Lagrange and the
Mean Value Theorem
3.
The Mean Value Theorem was first formulated by Joseph-Louis Lagrange
(1736–1813), born in Italy of a French
father and an Italian mother. He was a
child prodigy and became a professor
in Turin at the age of 19. Lagrange
made great contributions to number
theory, theory of functions, theory of
equations, and analytical and celestial
mechanics. In particular, he applied calculus to the analysis of the stability of
the solar system. At the invitation of
Frederick the Great, he succeeded Euler
at the Berlin Academy and, when
Frederick died, Lagrange accepted King
Louis XVI’s invitation to Paris, where he
was given apartments in the Louvre
and became a professor at the Ecole
Polytechnique. Despite all the trappings of luxury and fame, he was a kind
and quiet man, living only for science.
y
y=˛-x
hsad − f sad 2 f sad 2
f sbd 2 f sad
sa 2 ad − 0
b2a
hsbd − f sbd 2 f sad 2
f sbd 2 f sad
sb 2 ad
b2a
293
− f sbd 2 f sad 2 f f sbd 2 f sadg − 0
Therefore hsad − hsbd.
Since h satisfies all the hypotheses of Rolle’s Theorem, that theorem says there is a
number c in sa, bd such that h9scd − 0. Therefore
0 − h9scd − f 9scd 2
and so
f 9scd −
f sbd 2 f sad
b2a
f sbd 2 f sad
b2a
n
EXAMPLE 3 To illustrate the Mean Value Theorem with a specific function, let’s
consider f sxd − x 3 2 x, a − 0, b − 2. Since f is a polynomial, it is continuous and
differentiable for all x, so it is certainly continuous on f0, 2g and differentiable on s0, 2d.
Therefore, by the Mean Value Theorem, there is a number c in s0, 2d such that
f s2d 2 f s0d − f 9scds2 2 0d
B
Now f s2d − 6, f s0d − 0, and f 9sxd − 3x 2 2 1, so the above equation becomes
6 − s3c 2 2 1d2 − 6c 2 2 2
O
c
FIGURE 6
The Mean Value Theorem
2
x
which gives c 2 − 43 , that is, c − 62ys3. But c must lie in s0, 2d, so c − 2ys3.
Figure 6 illustrates this calculation: the tangent line at this value of c is parallel to the
secant line OB.
n
EXAMPLE 4 If an object moves in a straight line with position function s − f std, then
the average velocity between t − a and t − b is
f sbd 2 f sad
b2a
and the velocity at t − c is f 9scd. Thus the Mean Value Theorem (in the form of
Equation 1) tells us that at some time t − c between a and b the instantaneous velocity
f 9scd is equal to that average velocity. For instance, if a car traveled 180 km in 2 hours,
then the speedometer must have read 90 kmyh at least once.
In general, the Mean Value Theorem can be interpreted as saying that there is a
number at which the instantaneous rate of change is equal to the average rate of change
over an interval.
n
The main significance of the Mean Value Theorem is that it enables us to obtain information about a function from information about its derivative. The next example provides an instance of this principle.
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294
CHAPTER 4
Applications of Differentiation
EXAMPLE 5 Suppose that f s0d − 23 and f 9sxd < 5 for all values of x. How large can
f s2d possibly be?
SOLUTION We are given that f is differentiable (and therefore continuous) everywhere.
In particular, we can apply the Mean Value Theorem on the interval f0, 2g. There exists
a number c such that
f s2d 2 f s0d − f 9scds2 2 0d
f s2d − f s0d 1 2f 9scd − 23 1 2f 9scd
so
We are given that f 9sxd < 5 for all x, so in particular we know that f 9scd < 5. Multiplying both sides of this inequality by 2, we have 2f 9scd < 10, so
f s2d − 23 1 2f 9scd < 23 1 10 − 7
The largest possible value for f s2d is 7.
n
The Mean Value Theorem can be used to establish some of the basic facts of differential calculus. One of these basic facts is the following theorem. Others will be discussed
in the following sections.
5 Theorem If f 9sxd − 0 for all x in an interval sa, bd, then f is constant on sa, bd.
PROOF Let x 1 and x 2 be any two numbers in sa, bd with x 1 , x 2 . Since f is differentiable on sa, bd, it must be differentiable on sx 1, x 2 d and continuous on fx 1, x 2 g. By
applying the Mean Value Theorem to f on the interval fx 1, x 2 g, we get a number c such
that x 1 , c , x 2 and
f sx 2 d 2 f sx 1d − f 9scdsx 2 2 x 1d
6
Since f 9sxd − 0 for all x, we have f 9scd − 0, and so Equation 6 becomes
f sx 2 d 2 f sx 1 d − 0
or
f sx 2 d − f sx 1 d
Therefore f has the same value at any two numbers x 1 and x 2 in sa, bd. This means that
f is constant on sa, bd.
n
Corollary 7 says that if two functions
have the same derivatives on an interval, then their graphs must be vertical
translations of each other there. In
other words, the graphs have the
same shape, but they could be shifted
up or down.
7 Corollary If f 9sxd − t9sxd for all x in an interval sa, bd, then f 2 t is constant
on sa, bd; that is, f sxd − tsxd 1 c where c is a constant.
PROOF Let Fsxd − f sxd 2 tsxd. Then
F9sxd − f 9sxd 2 t9sxd − 0
for all x in sa, bd. Thus, by Theorem 5, F is constant; that is, f 2 t is constant.
n
NOTE Care must be taken in applying Theorem 5. Let
f sxd −
H
x
1
if x . 0
−
x
21 if x , 0
| |
|
The domain of f is D − hx x ± 0j and f 9sxd − 0 for all x in D. But f is obviously not
a constant function. This does not contradict Theorem 5 because D is not an interval.
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SECTION 4.2
295
The Mean Value Theorem
EXAMPLE 6 Prove the identity tan21 x 1 cot21 x − !y2.
SOLUTION Although calculus isn’t needed to prove this identity, the proof using
calculus is quite simple. If f sxd − tan21 x 1 cot21 x, then
f 9sxd −
1
1
2
−0
1 1 x2
1 1 x2
for all values of x. Therefore f sxd − C, a constant. To determine the value of C, we put
x − 1 [because we can evaluate f s1d exactly]. Then
!
!
!
C − f s1d − tan21 1 1 cot21 1 −
1
−
4
4
2
Thus tan21 x 1 cot21 x − !y2.
n
4.2 Exercises
1. The graph of a function f is shown. Verify that f satisfies the
hypotheses of Rolle’s Theorem on the interval f0, 8g. Then
estimate the value(s) of c that satisfy the conclusion of Rolle’s
Theorem on that interval.
5–8 The graph of a function f is shown. Does f satisfy the
hypotheses of the Mean Value Theorem on the interval f0, 5g? If
so, find a value c that satisfies the conclusion of the Mean Value
Theorem on that interval.
5.
y
6.
y
1
1
0
y
y=ƒ
0
1
x
1
0
1
x
x
1
7.
2. Draw the graph of a function defined on f0, 8g such that
f s0d − f s8d − 3 and the function does not satisfy the conclusion of Rolle’s Theorem on f0, 8g.
3. The graph of a function t is shown.
8.
y
1
0
y
1
1
x
0
1
x
y
y=©
9–12 Verify that the function satisfies the three hypotheses of
Rolle’s Theorem on the given interval. Then find all numbers c
that satisfy the conclusion of Rolle’s Theorem.
1
0
9. f sxd − 2 x 2 2 4 x 1 5, f21, 3g
1
x
(a) Verify that t satisfies the hypotheses of the Mean Value
Theorem on the interval f0, 8g.
(b) Estimate the value(s) of c that satisfy the conclusion of
the Mean Value Theorem on the interval f0, 8g.
(c) Estimate the value(s) of c that satisfy the conclusion of
the Mean Value Theorem on the interval f2, 6g.
4. Draw the graph of a function that is continuous on f0, 8g
where f s0d − 1 and f s8d − 4 and that does not satisfy the
conclusion of the Mean Value Theorem on f0, 8g.
10. f sxd − x 3 2 2x 2 2 4x 1 2, f22, 2g
11. f sxd − sins xy2d, f!y2, 3!y2g
12. f sxd − x 1 1y x,
f 12 , 2g
13. Let f sxd − 1 2 x 2y3. Show that f s21d − f s1d but there is no
number c in s21, 1d such that f 9scd − 0. Why does this not
contradict Rolle’s Theorem?
14. Let f sxd − tan x. Show that f s0d − f s!d but there is no number c in s0, !d such that f 9scd − 0. Why does this not contradict Rolle’s Theorem?
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296
CHAPTER 4
Applications of Differentiation
15–18 Verify that the function satisfies the hypotheses of the
Mean Value Theorem on the given interval. Then find all
numbers c that satisfy the conclusion of the Mean Value
Theorem.
15. f sxd − 2x 2 2 3x 1 1,
f0, 2g
16. f sxd − x 2 3x 1 2, f22, 2g
3
17. f sxd − ln x,
f1, 4g
18. f sxd − 1yx, f1, 3g
30. Suppose that 3 < f 9sxd < 5 for all values of x. Show that
18 < f s8d 2 f s2d < 30.
31. Does there exist a function f such that f s0d − 21,
f s2d − 4, and f 9sxd < 2 for all x ?
32. Suppose that f and t are continuous on fa, bg and differentiable on sa, bd. Suppose also that f sad − tsad and
f 9sxd , t9sxd for a , x , b. Prove that f sbd , tsbd. [Hint:
Apply the Mean Value Theorem to the function h − f 2 t.]
33. Show that sin x , x if 0 , x , 2!.
; 19–20 Find the number c that satisfies the conclusion of the
Mean Value Theorem on the given interval. Graph the function, the secant line through the endpoints, and the tangent line
at sc, f scdd. Are the secant line and the tangent line parallel?
19. f sxd − sx ,
f0, 4g
20. f sxd − e2x, f0, 2g
21. Let f sxd − s x 2 3d22. Show that there is no value of c in
s1, 4d such that f s4d 2 f s1d − f 9scds4 2 1d. Why does this
not contradict the Mean Value Theorem?
|
34. Suppose f is an odd function and is differentiable everywhere. Prove that for every positive number b, there exists
a number c in s2b, bd such that f 9scd − f sbdyb.
35. Use the Mean Value Theorem to prove the inequality
| sin a 2 sin b | < | a 2 b |
36. If f 9sxd − c (c a constant) for all x, use Corollary 7 to show
that f sxd − cx 1 d for some constant d.
37. Let f sxd − 1yx and
|
22. Let f sxd − 2 2 2 x 2 1 . Show that there is no value of c
such that f s3d 2 f s0d − f 9scds3 2 0d. Why does this not
contradict the Mean Value Theorem?
1
x
tsxd −
24. x 3 1 e x − 0
25. Show that the equation x 3 2 15x 1 c − 0 has at most one
solution in the interval f22, 2g.
4
26. Show that the equation x 1 4x 1 c − 0 has at most two
real solutions.
27. (a) Show that a polynomial of degree 3 has at most three
real zeros.
(b) Show that a polynomial of degree n has at most n real
zeros.
28. (a) Suppose that f is differentiable on R and has two zeros.
Show that f 9 has at least one zero.
(b) Suppose f is twice differentiable on R and has three
zeros. Show that f 0 has at least one real zero.
(c) Can you generalize parts (a) and (b)?
29. If f s1d − 10 and f 9sxd > 2 for 1 < x < 4, how small can
f s4d possibly be?
if x . 0
11
23–24 Show that the equation has exactly one real solution.
23. 2 x 1 cos x − 0
for all a and b
1
x
if x , 0
Show that f 9sxd − t9sxd for all x in their domains. Can we
conclude from Corollary 7 that f 2 t is constant?
38–39 Use the method of Example 6 to prove the identity.
SD
38. arctan x 1 arctan
1
x
−
!
,
2
39. 2 sin21x − cos21s1 2 2x 2 d,
x.0
x>0
40. At 2:00 pm a car’s speedometer reads 30 miyh. At 2:10 pm it
reads 50 miyh. Show that at some time between 2:00 and
2:10 the acceleration is exactly 120 miyh2.
41. Two runners start a race at the same time and finish in a tie.
Prove that at some time during the race they have the same
speed. [Hint: Consider f std − tstd 2 hstd, where t and h
are the position functions of the two runners.]
42. Fixed Points A number a is called a fixed point of a function f if f sad − a. Prove that if f 9sxd ± 1 for all real numbers x, then f has at most one fixed point.
4.3 What Derivatives Tell Us about the Shape of a Graph
Many of the applications of calculus depend on our ability to deduce facts about a function f from information concerning its derivatives. Because f 9sxd represents the slope of
the curve y − f sxd at the point sx, f sxdd, it tells us the direction in which the curve
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SECTION 4.3
y
297
proceeds at each point. So it is reasonable to expect that information about f 9sxd will
provide us with information about f sxd.
D
B
■ What Does f 9 Say about f ?
C
A
What Derivatives Tell Us about the Shape of a Graph
x
0
FIGURE 1
Notation
Let’s abbreviate the name of this test
to the I/D Test.
To see how the derivative of f can tell us where a function is increasing or decreasing,
look at Figure 1. (Increasing functions and decreasing functions were defined in Section 1.1.) Between A and B and between C and D, the tangent lines have positive slope
and so f 9sxd . 0. Between B and C, the tangent lines have negative slope and so
f 9sxd , 0. Thus it appears that f increases when f 9sxd is positive and decreases when
f 9sxd is negative. To prove that this is always the case, we use the Mean Value
Theorem.
Increasing/Decreasing Test
(a) If f 9sxd . 0 on an interval, then f is increasing on that interval.
(b) If f 9sxd , 0 on an interval, then f is decreasing on that interval.
PROOF
(a) Let x 1 and x 2 be any two numbers in the interval with x1 , x2. According
to the definition of an increasing function (Section 1.1), we have to show that
f sx1 d , f sx2 d.
Because we are given that f 9sxd . 0, we know that f is differentiable on fx1, x2 g.
So, by the Mean Value Theorem, there is a number c between x1 and x2 such that
f sx 2 d 2 f sx 1 d − f 9scdsx 2 2 x 1 d
1
Now f 9scd . 0 by assumption and x 2 2 x 1 . 0 because x 1 , x 2. Thus the right side of
Equation 1 is positive, and so
f sx 2 d 2 f sx 1 d . 0
or
f sx 1 d , f sx 2 d
This shows that f is increasing.
Part (b) is proved similarly.
n
EXAMPLE 1 Find where the function f sxd − 3x 4 2 4x 3 2 12x 2 1 5 is increasing
and where it is decreasing.
SOLUTION We start by differentiating f :
f 9sxd − 12x 3 2 12x 2 2 24x − 12xsx 2 2dsx 1 1d
_1
FIGURE 2
0
2
x
To use the IyD Test we have to know where f 9sxd . 0 and where f 9sxd , 0. To solve
these inequalities we first find where f 9sxd − 0, namely at x − 0, 2, and 21. These
are the critical numbers of f , and they divide the domain into four intervals (see the
number line in Figure 2). Within each interval, f 9sxd must be always positive or
always negative. (See Examples 3 and 4 in Appendix A.) We can determine which is
the case for each interval from the signs of the three factors of f 9sxd, namely, 12x,
x 2 2, and x 1 1, as shown in the following chart. A plus sign indicates that the
given expression is positive, and a minus sign indicates that it is negative. The last
column of the chart gives the conclusion based on the IyD Test. For instance,
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298
CHAPTER 4
Applications of Differentiation
f 9sxd , 0 for 0 , x , 2, so f is decreasing on (0, 2). (It would also be true to say
that f is decreasing on the closed interval f0, 2g.)
20
_2
3
_30
FIGURE 3
Interval
12x
x22
x11
f 9sxd
f
x , 21
21 , x , 0
0,x,2
x.2
2
2
1
1
2
2
2
1
2
1
1
1
2
1
2
1
decreasing on s2`, 21d
increasing on s21, 0d
decreasing on s0, 2d
increasing on s2, `d
The graph of f shown in Figure 3 confirms the information in the chart.
n
■ The First Derivative Test
Recall from Section 4.1 that if f has a local maximum or minimum at c, then c must be
a critical number of f (by Fermat’s Theorem), but not every critical number gives rise
to a maximum or a minimum. We therefore need a test that will tell us whether or not
f has a local maximum or minimum at a critical number.
You can see from Figure 3 that for the function f in Example 1, f s0d − 5 is a local
maximum value of f because f increases on s21, 0d and decreases on s0, 2d. Or, in terms
of derivatives, f 9sxd . 0 for 21 , x , 0 and f 9sxd , 0 for 0 , x , 2. In other words,
the sign of f 9sxd changes from positive to negative at 0. This observation is the basis of
the following test.
The First Derivative Test Suppose that c is a critical number of a continuous
function f.
(a) If f 9 changes from positive to negative at c, then f has a local maximum at c.
(b) If f 9 changes from negative to positive at c, then f has a local minimum at c.
(c) If f 9 is positive to the left and right of c, or negative to the left and right of c,
then f has no local maximum or minimum at c.
The First Derivative Test is a consequence of the IyD Test. In part (a), for instance,
because the sign of f 9sxd changes from positive to negative at c, f is increasing to the left
of c and decreasing to the right of c. It follows that f has a local maximum at c.
It is easy to remember the First Derivative Test by visualizing diagrams such as those
in Figure 4.
y
y
fª(x)>0
y
fª(x)<0
fª(x)<0
fª(x)>0
fª(x)<0
0
c
(a) Local maximum at c
y
x
0
fª(x)>0
c
(b) Local minimum at c
fª(x)<0
fª(x)>0
x
0
c
x
(c) No maximum or minimum at c
0
c
x
(d) No maximum or minimum at c
FIGURE 4
EXAMPLE 2 Find the local minimum and maximum values of the function f in
Example 1.
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SECTION 4.3
299
What Derivatives Tell Us about the Shape of a Graph
SOLUTION From the chart in the solution to Example 1 we see that f 9sxd changes
from negative to positive at 21, so f s21d − 0 is a local minimum value by the First
Derivative Test. Similarly, f 9 changes from negative to positive at 2, so f s2d − 227 is
also a local minimum value. As noted previously, f s0d − 5 is a local maximum value
because f 9sxd changes from positive to negative at 0.
n
EXAMPLE 3 Find the local maximum and minimum values of the function
tsxd − x 1 2 sin x
0 < x < 2!
SOLUTION As in Example 1, we start by finding the critical numbers. The derivative is:
t9sxd − 1 1 2 cos x
so t9sxd − 0 when cos x − 212. The solutions of this equation are 2!y3 and 4!y3.
Because t is differentiable everywhere, the only critical numbers are 2!y3 and 4!y3.
We split the domain into intervals according to the critical numbers. Within each
interval, t9sxd is either always positive or always negative and so we analyze t in the
following chart.
The 1 signs in the chart come from
the fact that t9sxd . 0 when
cos x . 212 . From the graph of
y − cos x, this is true in the indicated
intervals. Alternatively, we can choose
a test value within each interval and
check the sign of t9sxd using that value.
t9sxd − 1 1 2 cos x
Interval
t
0 , x , 2!y3
1
increasing on s0, 2!y3d
2!y3 , x , 4!y3
2
decreasing on s2!y3, 4!y3d
4!y3 , x , 2!
1
increasing on s4!y3, 2!d
Because t9sxd changes from positive to negative at 2!y3, the First Derivative Test
tells us that there is a local maximum at 2!y3 and the local maximum value is
6
ts2!y3d −
S D
2!
2!
2!
s3
1 2 sin
−
12
3
3
3
2
−
2!
1 s3 < 3.83
3
Likewise, t9sxd changes from negative to positive at 4!y3 and so
0
2π
3
4π
3
2π
ts4!y3d −
S D
4!
4!
4!
s3
1 2 sin
−
12 2
3
3
3
2
−
4!
2 s3 < 2.46
3
is a local minimum value. The graph of t in Figure 5 supports our conclusion.
FIGURE 5
tsxd − x 1 2 sin x
n
■ What Does f 99 Say about f ?
Figure 6 shows the graphs of two increasing functions on sa, bd. Both graphs join point A
to point B but they look different because they bend in different directions. How can
we distinguish between these two types of behavior?
B
y
B
y
g
f
A
A
0
FIGURE 6
b
a
(a)
x
0
b
a
(b)
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
x
300
CHAPTER 4
Applications of Differentiation
In Figure 7 tangents to these curves have been drawn at several points. In part (a)
the curve lies above the tangents and f is called concave upward on sa, bd. In part (b) the
curve lies below the tangents and t is called concave downward on sa, bd.
B
y
B
y
g
f
A
0
FIGURE 7
Notation
We use the abbreviation CU for concave upward and CD for concave
downward.
A
a
0
x
b
a
x
b
(b) Concave downward
(a) Concave upward
Definition If the graph of f lies above all of its tangents on an interval I, then f
is called concave upward on I. If the graph of f lies below all of its tangents on I,
then f is called concave downward on I.
Figure 8 shows the graph of a function that is concave upward (CU) on the intervals sb, cd, sd, ed, and se, pd and concave downward (CD) on the intervals sa, bd, sc, dd,
and sp, qd.
y
D
B
0 a
FIGURE 8
b
CD
P
C
c
CU
d
CD
e
CU
p
CU
q
x
CD
Let’s see how the second derivative helps determine the intervals of concavity. Looking at Figure 7(a), you can see that, going from left to right, the slope of the tangent
increases. This means that the derivative f 9 is an increasing function and therefore its
derivative f 0 is positive. Likewise, in Figure 7(b) the slope of the tangent decreases from
left to right, so f 9 decreases and therefore f 0 is negative. This reasoning can be reversed
and suggests that the following theorem is true. A proof is given in Appendix F with the
help of the Mean Value Theorem.
Concavity Test
(a) If f 0sxd . 0 on an interval I, then the graph of f is concave upward on I.
(b) If f 0sxd , 0 on an interval I, then the graph of f is concave downward on I.
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SECTION 4.3
What Derivatives Tell Us about the Shape of a Graph
301
EXAMPLE 4 Figure 9 shows a population graph for honeybees raised in an apiary.
How does the rate of population growth change over time? When is this rate highest?
Over what intervals is P concave upward or concave downward?
P
80
Number of bees
(in thousands)
60
40
20
0
3
6
9
12
15
18
t
Time (in weeks)
FIGURE 9
SOLUTION By looking at the slope of the curve as t increases, we see that the rate of
growth of the population is initially very small, then gets larger until it reaches a
maximum at about t − 12 weeks, and decreases as the population begins to level off.
As the population approaches its maximum value of about 75,000 (called the carrying
capacity), the rate of growth, P9std, approaches 0. The curve appears to be concave
upward on (0, 12) and concave downward on (12, 18).
n
In Example 4, the population curve changed from concave upward to concave downward at approximately the point (12, 38,000). This point is called an inflection point of
the curve. The significance of this point is that the rate of population increase has its
maximum value there. In general, an inflection point is a point where a curve changes its
direction of concavity.
Definition A point P on a curve y − f sxd is called an inflection point if f is continuous there and the curve changes from concave upward to concave downward
or from concave downward to concave upward at P.
For instance, in Figure 8, B, C, D, and P are the points of inflection. Notice that if a
curve has a tangent at a point of inflection, then the curve crosses its tangent there.
In view of the Concavity Test, there is a point of inflection at any point where the
function is continuous and the second derivative changes sign.
EXAMPLE 5 Sketch a possible graph of a function f that satisfies the following
conditions:
sid f 9sxd . 0 on s2`, 1d, f 9sxd , 0 on s1, `d
siid f 0sxd . 0 on s2`, 22d and s2, `d, f 0sxd , 0 on s22, 2d
siiid lim f sxd − 22, lim f sxd − 0
x l 2`
x l`
SOLUTION Condition (i) tells us that f is increasing on s2`, 1d and decreasing
on s1, `d. Condition (ii) says that f is concave upward on s2`, 22d and s2, `d, and
concave downward on s22, 2d. From condition (iii) we know that the graph of f has
two horizontal asymptotes: y − 22 (to the left) and y − 0 (to the right).
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302
CHAPTER 4
Applications of Differentiation
y
_2
0
1
We first draw the horizontal asymptote y − 22 as a dashed line (see Figure 10). We
then draw the graph of f approaching this asymptote at the far left, increasing to its
maximum point at x − 1, and decreasing toward the x-axis at the far right. We also
x make sure that the graph has inflection points when x − 22 and 2. Notice that we
made the curve bend upward for x , 22 and x . 2, and bend downward when x is
between 22 and 2.
n
2
y=_2
FIGURE 10
■ The Second Derivative Test
Another application of the second derivative is the following test for identifying local
maximum and minimum values. It is a consequence of the Concavity Test, and it serves
as an alternative to the First Derivative Test.
The Second Derivative Test Suppose f 0 is continuous near c.
(a) If f 9scd − 0 and f 0scd . 0, then f has a local minimum at c.
(b) If f 9scd − 0 and f 0scd , 0, then f has a local maximum at c.
y
f
P
For instance, part (a) is true because f 0sxd . 0 near c and so f is concave upward
near c. This means that the graph of f lies above its horizontal tangent at c and so f has
a local minimum at c. (See Figure 11.)
f ª(c)=0
c
0
FIGURE 11
f 99scd . 0, f is concave upward
x
NOTE The Second Derivative Test is inconclusive when f 0scd − 0. In other words, at
such a point there might be a maximum, there might be a minimum, or there might be
neither. This test also fails when f 0scd does not exist. In such cases the First Derivative
Test must be used. In fact, even when both tests apply, the First Derivative Test is often
the easier one to use.
EXAMPLE 6 Discuss the curve y − x 4 2 4x 3 with respect to concavity, points of
inflection, and local maxima and minima.
SOLUTION If f sxd − x 4 2 4x 3, then
f 9sxd − 4x 3 2 12x 2 − 4x 2sx 2 3d
f 0sxd − 12x 2 2 24x − 12xsx 2 2d
To find the critical numbers we set f 9sxd − 0 and obtain x − 0 and x − 3. (Note that f 9
is a polynomial and hence defined everywhere.) To use the Second Derivative Test we
evaluate f 0 at these critical numbers:
f 0s0d − 0
f 0s3d − 36 . 0
Since f 9s3d − 0 and f 0s3d . 0, the Second Derivative Test tells us that f s3d − 227
is a local minimum. Because f 0s0d − 0, the Second Derivative Test gives no information about the critical number 0. But since f 9sxd , 0 for x , 0 and also for
0 , x , 3, the First Derivative Test tells us that f does not have a local maximum or
minimum at 0.
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SECTION 4.3
What Derivatives Tell Us about the Shape of a Graph
303
Since f 0sxd − 0 when x − 0 or 2, we divide the real line into intervals with these
numbers as endpoints and complete the following chart.
15
_2
5
_30
FIGURE 12
y − x 4 2 4x 3
Interval
f 99sxd − 12 x sx 2 2d
Concavity
s2`, 0d
1
upward
s0, 2d
2
downward
s2, `d
1
upward
The point s0, 0d is an inflection point because the curve changes from concave
upward to concave downward there. Also s2, 216d is an inflection point because the
curve changes from concave downward to concave upward there.
The graph of y − x 4 2 4x 3 in Figure 12 supports our conclusions.
n
■ Curve Sketching
We now use the information we obtain from the first and second derivatives to sketch the
graph of a function.
EXAMPLE 7 Sketch the graph of the function f sxd − x 2y3s6 2 xd1y3.
Use the differentiation rules to check
these calculations.
SOLUTION First note that the domain of f is R. Calculation of the first two derivatives
gives
42x
28
f 9sxd − 1y3
f 0sxd − 4y3
x s6 2 xd2y3
x s6 2 xd5y3
Since f 9sxd − 0 when x − 4 and f 9sxd does not exist when x − 0 or x − 6, the critical
numbers are 0, 4, and 6.
42x
x 1y3
s6 2 xd2y3
f 9sxd
f
x,0
1
2
1
2
decreasing on s2`, 0d
0,x,4
1
1
1
1
increasing on s0, 4d
4,x,6
2
1
1
2
decreasing on s4, 6d
x.6
2
1
1
2
decreasing on s6, `d
Interval
To find the local extreme values we use the First Derivative Test. Since f 9 changes
from negative to positive at 0, f s0d − 0 is a local minimum. Since f 9 changes from positive to negative at 4, f s4d − 2 5y3 is a local maximum. The sign of f 9 does not change
at 6, so there is no minimum or maximum there. (The Second Derivative Test could be
used at 4 but not at 0 or 6 because f 0 does not exist at either of these numbers.)
Looking at the expression for f 0sxd and noting that x 4y3 > 0 for all x, we have
f 0sxd , 0 for x , 0 and for 0 , x , 6 and f 0sxd . 0 for x . 6. So f is concave
downward on s2`, 0d and s0, 6d and concave upward on s6, `d, and the only inflection
point is s6, 0d. Using all of the information we gathered about f from its first and
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304
CHAPTER 4
Applications of Differentiation
Try reproducing the graph in Figure 13
with a graphing calculator or computer. Some machines produce the
complete graph, some produce only
the portion to the right of the y-axis,
and some produce only the portion
between x − 0 and x − 6. For an
explanation, see Example 7 in Graphing Calculators and Computers at
www.StewartCalculus.com.
second derivatives, we sketch the graph in Figure 13. Note that the curve has vertical
tangents at s0, 0d and s6, 0d because f 9sxd l ` as x l 0 and as x l 6.
|
|
y
4
(4, 2%?#)
3
2
0
1
2
3
4
5
7
x
y=x @ ?#(6-x)!?#
FIGURE 13
n
EXAMPLE 8 Use the first and second derivatives of f sxd − e 1yx, together with
asymptotes, to sketch its graph.
|
SOLUTION Notice that the domain of f is hx x ± 0j, so we check for vertical
asymptotes by computing the left and right limits as x l 0. As x l 01, we know that
t − 1yx l `, so
lim e 1yx − lim e t − `
x l 01
tl`
and this shows that x − 0 is a vertical asymptote. As x l 02, we have
t − 1yx l 2`, so
lim e 1yx − lim e t − 0
x l 02
t l2`
As x l 6`, we have 1yx l 0 and so
lim e 1yx − e 0 − 1
x l 6`
This shows that y − 1 is a horizontal asymptote (to both the left and right).
Now let’s compute the derivative. The Chain Rule gives
f 9sxd − 2
e 1yx
x2
Since e 1yx . 0 and x 2 . 0 for all x ± 0, we have f 9sxd , 0 for all x ± 0. Thus f is
decreasing on s2`, 0d and on s0, `d. There is no critical number, so the function has no
local maximum or minimum. The second derivative is
f 0sxd − 2
x 2e 1yxs21yx 2 d 2 e 1yxs2xd
e 1yxs2x 1 1d
−
4
x
x4
Since e 1yx . 0 and x 4 . 0, we have f 0sxd . 0 when x . 212 sx ± 0d and f 0sxd , 0
when x , 212. So the curve is concave downward on (2`, 212 ) and concave upward on
(212 , 0) and on s0, `d. There is one inflection point: (212 , e22).
To sketch the graph of f we first draw the horizontal asymptote y − 1 (as a dashed
line), together with the parts of the curve near the asymptotes in a preliminary sketch
[Figure 14(a)]. These parts reflect the information concerning limits and the fact
that f is decreasing on both s2`, 0d and s0, `d. Notice that we have indicated that
f sxd l 0 as x l 02 even though f s0d does not exist. In Figure 14(b) we finish the
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.3
305
What Derivatives Tell Us about the Shape of a Graph
sketch by incorporating the information concerning concavity and the inflection point.
In Figure 14(c) we check our work with a computer.
y
y
y=‰
4
inflection
point
y=1
0
y=1
0
x
(a) Preliminary sketch
_3
3
x
_1
(b) Finished sketch
(c) Computer confirmation
FIGURE 14
n
4.3 Exercises
1–2 Use the given graph of f to find the following.
(a) The open intervals on which f is increasing.
(b) The open intervals on which f is decreasing.
(c) The open intervals on which f is concave upward.
(d) The open intervals on which f is concave downward.
(e) The coordinates of the points of inflection.
1.
y
6.
0
1
1
0
x
1
1
x
3. Suppose you are given a formula for a function f.
(a) How do you determine where f is increasing or decreasing?
(b) How do you determine where the graph of f is concave
upward or concave downward?
(c) How do you locate inflection points?
4. (a) State the First Derivative Test.
(b) State the Second Derivative Test. Under what circumstances is it inconclusive? What do you do if it fails?
5–6 The graph of the derivative f 9 of a function f is shown.
(a) On what intervals is f increasing? Decreasing?
(b) At what values of x does f have a local maximum? Local
minimum?
5.
y
0
4
2
4
6
x
6
7. In each part state the x-coordinates of the inflection points
of f. Give reasons for your answers.
(a) The curve is the graph of f .
(b) The curve is the graph of f 9.
(c) The curve is the graph of f 0.
y
0
2
x
4
6
x
8
8. The graph of the first derivative f 9 of a function f is shown.
(a) On what intervals is f increasing? Explain.
(b) At what values of x does f have a local maximum or
minimum? Explain.
(c) On what intervals is f concave upward or concave
downward? Explain.
(d) What are the x-coordinates of the inflection points of f ?
Why?
y
y=fª(x)
2
y=fª(x)
y
2.
0
y
0
y=fª(x)
2
4
6
8
x
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
306
CHAPTER 4
Applications of Differentiation
9–16 Find the intervals on which f is increasing or decreasing,
and find the local maximum and minimum values of f .
34–41 Sketch the graph of a function that satisfies all of the given
conditions.
9. f sxd − 2x 3 2 15x 2 1 24x 2 5
34. (a) f 9sxd , 0 and f 0sxd , 0 for all x
(b) f 9sxd . 0 and f 0sxd . 0 for all x
10. f sxd − x 2 6x 2 135x
3
2
11. f sxd − 6x 4 2 16x 3 1 1
13. f sxd −
12. f sxd − x 2y3sx 2 3d
x 2 2 24
x25
14. f sxd − x 1
4
x2
15. f sxd − sin x 1 cos x, 0 < x < 2!
16. f sxd − x 4 e2x
17–22 Find the intervals on which f is concave upward or
concave downward, and find the inflection points of f .
17. f sxd − x 3 2 3x 2 2 9x 1 4
36. Vertical asymptote x − 0, f 9sxd . 0 if x , 22,
f 9sxd , 0 if x . 22 sx ± 0d,
f 0sxd , 0 if x , 0, f 0sxd . 0 if x . 0
37. f 9s0d − f 9s2d − f 9s4d − 0,
f 9sxd . 0 if x , 0 or 2 , x , 4,
f 9sxd , 0 if 0 , x , 2 or x . 4,
f 0sxd . 0 if 1 , x , 3, f 0sxd , 0 if x , 1 or x . 3
38. f 9sxd . 0 for all x ± 1, vertical asymptote x − 1,
f 99sxd . 0 if x , 1 or x . 3, f 99sxd , 0 if 1 , x , 3
18. f sxd − 2x 3 2 9x 2 1 12x 2 3
19. f sxd − sin2x 2 cos 2x, 0 < x < !
20. f sxd − lns2 1 sin xd, 0 < x < 2!
21. f sxd − lnsx 2 1 5d
35. (a) f 9sxd . 0 and f 0sxd , 0 for all x
(b) f 9sxd , 0 and f 0sxd . 0 for all x
22. f sxd −
ex
e 12
x
39. f 9s5d − 0, f 9sxd , 0 when x , 5,
f 9sxd . 0 when x . 5, f 99s2d − 0, f 99s8d − 0,
f 99sxd , 0 when x , 2 or x . 8,
f 99sxd . 0 for 2 , x , 8, lim f sxd − 3, lim f sxd − 3
xl`
23–28
(a) Find the intervals on which f is increasing or decreasing.
(b) Find the local maximum and minimum values of f .
(c) Find the intervals of concavity and the inflection points.
23. f sxd − x 4 2 2x 2 1 3
x
24. f sxd − 2
x 11
25. f sxd − x 2 2 x 2 ln x
26. f sxd − x 2 ln x
27. f sxd − xe 2x
28. f sxd − cos2 x 2 2 sin x,
29–30 Find the local maximum and minimum values of f using
both the First and Second Derivative Tests. Which method do you
prefer?
x2
29. f sxd − 1 1 3x 2 2 2x 3
30. f sxd −
x21
31. Suppose the derivative of a function f is
f 9sxd − sx 2 4d sx 1 3d sx 2 5d
2
7
x l2
x l2
f 99sxd . 0 if 21 , x , 2 or 2 , x , 4,
f 0sxd , 0 if x . 4
41. f 9sxd . 0 if x ± 2, f 99sxd . 0 if x , 2,
f 99sxd , 0 if x . 2, f has inflection point s2, 5d,
lim f sxd − 8, lim f sxd − 0
xl`
0 < x < 2!
8
On what interval(s) is f increasing?
32. (a) Find the critical numbers of f sxd − x 4sx 2 1d3.
(b) What does the Second Derivative Test tell you about the
behavior of f at these critical numbers?
(c) What does the First Derivative Test tell you?
33. Suppose f 0 is continuous on s2`, `d.
(a) If f 9s2d − 0 and f 0s2d − 25, what can you say about f ?
(b) If f 9s6d − 0 and f 0s6d − 0, what can you say about f ?
xl 2`
40. f 9s0d − f 9s4d − 0, f 9sxd − 1 if x , 21,
f 9sxd . 0 if 0 , x , 2,
f 9sxd , 0 if 21 , x , 0 or 2 , x , 4 or x . 4,
lim2 f 9sxd − `, lim1 f 9sxd − 2`,
xl 2`
42. The graph of a function y − f sxd is shown. At which point(s)
are the following true?
(a)
dy
d 2y
and
are both positive.
dx
dx 2
(b)
dy
d 2y
and
are both negative.
dx
dx 2
(c)
dy
d 2y
is negative but
is positive.
dx
dx 2
y
C
A
0
D
E
B
x
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.3
43–44 The graph of the derivative f 9 of a continuous function f
is shown.
(a) On what intervals is f increasing? Decreasing?
(b) At what values of x does f have a local maximum? Local
minimum?
(c) On what intervals is f concave upward? Concave downward?
(d) State the x-coordinate(s) of the point(s) of inflection.
(e) Assuming that f s0d − 0, sketch a graph of f .
43.
y
y=fª(x)
2
0
y
2
4
6
63. f sxd − e 2x
62. f sxd −
ex
1 2 ex
64. f sxd − x 2 16 x 2 2 23 ln x
2
65. f sxd − lns1 2 ln xd
66. f sxd − e arctan x
67–68 Use the methods of this section to sketch several members
of the given family of curves. What do the members have in
common? How do they differ from each other?
68. f sxd − x 3 2 3c 2 x 1 2c 3,
8 x
y=fª(x)
2
4
6
69. f sxd −
8 x
_2
45–58
(a) Find the intervals of increase or decrease.
(b) Find the local maximum and minimum values.
(c) Find the intervals of concavity and the inflection points.
(d) Use the information from parts (a) – (c) to sketch the graph.
You may want to check your work with a graphing calculator
or computer.
45. f sxd − x 3 2 3x 2 1 4
46. f sxd − 36x 1 3x 2 2 2x 3
47. f sxd − 12 x 4 2 4x 2 1 3
48. tsxd − 200 1 8x 3 1 x 4
49. tstd − 3t 2 8t 1 12
50. hsxd − 5x 2 3x
51. f szd − z 7 2 112z 2
52. f sxd − sx 2 2 4d3
53. Fsxd − x s6 2 x
54. Gsxd − 5x 2y3 2 2x 5y3
55. Csxd − x 1y3sx 1 4d
56. f sxd − lnsx 2 1 9d
57. f s"d − 2 cos " 1 cos 2",
0 < " < 2!
4
3
58. Ssxd − x 2 sin x,
3
60. f sxd −
x2 2 4
x2 1 4
70. f s xd − x 2 e2x
sx 2 1 1
; 71–72
(a) Use a graph of f to give a rough estimate of the intervals of
concavity and the coordinates of the points of inflection.
(b) Use a graph of f 0 to give better estimates.
71. f sxd − sin 2x 1 sin 4x,
72. f sxd − sx 2 1d sx 1 1d
2
0<x<!
3
73–74 Estimate the intervals of concavity to one decimal place by
using a computer algebra system to compute and graph f 0.
73. f sxd −
x4 1 x3 1 1
74. f sxd −
sx 2 1 x 1 1
x 2 tan21 x
1 1 x3
75. A graph of a population of yeast cells in a new laboratory culture as a function of time is shown.
Number
of
yeast cells
0 < x < 4!
1
1
2 2
x
x
x11
5
59–66
(a) Find the vertical and horizontal asymptotes.
(b) Find the intervals of increase or decrease.
(c) Find the local maximum and minimum values.
(d) Find the intervals of concavity and the inflection points.
(e) Use the information from parts (a) – (d) to sketch the graph of f.
59. f sxd − 1 1
c.0
; 69–70
(a) Use a graph of f to estimate the maximum and minimum
values. Then find the exact values.
(b) Estimate the value of x at which f increases most rapidly.
Then find the exact value.
2
0
61. f sxd − e22yx
307
67. f sxd − x 4 2 cx, c . 0
_2
44.
What Derivatives Tell Us about the Shape of a Graph
700
600
500
400
300
200
100
0
2
4
6
8
10 12 14 16 18
Time (in hours)
(a) Describe how the rate of population increase varies.
(b) When is this rate highest?
(c) On what intervals is the population function concave
upward or downward?
(d) Estimate the coordinates of the inflection point.
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
308
CHAPTER 4
Applications of Differentiation
76. In an episode of The Simpsons television show, Homer
reads from a newspaper and announces “Here’s good news!
According to this eye-catching article, SAT scores are
declining at a slower rate.” Interpret Homer’s statement in
terms of a function and its first and second derivatives.
77. The president announces that the national deficit is increasing, but at a decreasing rate. Interpret this statement in
terms of a function and its first and second derivatives.
78. Let f std be the temperature at time t where you live and
suppose that at time t − 3 you feel uncomfortably hot. How
do you feel about the given data in each case?
(a) f 9s3d − 2, f 0s3d − 4
(b) f 9s3d − 2, f 0s3d − 24
(c) f 9s3d − 22, f 0s3d − 4
(d) f 9s3d − 22, f 0s3d − 24
79. Let Kstd be a measure of the knowledge you gain by
studying for a test for t hours. Which do you think is larger,
Ks8d 2 Ks7d or Ks3d 2 Ks2d? Is the graph of K concave
upward or concave downward? Why?
80. Coffee is being poured into the mug shown in the figure at a
constant rate (measured in volume per unit time). Sketch a
rough graph of the depth of the coffee in the mug as a function of time. Account for the shape of the graph in terms of
concavity. What is the significance of the inflection point?
; 81. A drug response curve describes the level of medication in
the bloodstream after a drug is administered. A surge function Sstd − At pe2kt is often used to model the response
curve, reflecting an initial surge in the drug level and then a
more gradual decline. If, for a particular drug, A − 0.01,
p − 4, k − 0.07, and t is measured in minutes, estimate the
times corresponding to the inflection points and explain
their significance. Then graph the drug response curve.
82. Normal Density Functions The family of bell-shaped curves
y−
1
& s2!
e2sx2#d ys2& d
2
2
occurs in probability and statistics, where it is called the normal density function. The constant # is called the mean and
the positive constant & is called the standard deviation. For
simplicity, let’s scale the function so as to remove the factor
1y(& s2! ) and let’s analyze the special case where # − 0.
So we study the function
;
(b) What role does & play in the shape of the curve?
(c) Illustrate by graphing four members of this family on
the same screen.
83. Find a cubic function f sxd − ax 3 1 bx 2 1 cx 1 d that
has a local maximum value of 3 at x − 22 and a local minimum value of 0 at x − 1.
84. For what values of the numbers a and b does the function
f sxd − axe bx
2
have the maximum value f s2d − 1?
85. Show that the curve y − s1 1 xdys1 1 x 2 d has three points
of inflection and they all lie on one straight line.
86. Show that the curves y − e 2x and y − 2e2x touch the curve
y − e2x sin x at its inflection points.
87. Show that the inflection points of the curve y − x sin x lie
on the curve y 2sx 2 1 4d − 4x 2.
88–90 Assume that all of the functions are twice differentiable
and the second derivatives are never 0.
88. (a) If f and t are concave upward on an interval I, show
that f 1 t is concave upward on I.
(b) If f is positive and concave upward on I, show that the
function tsxd − f f sxdg 2 is concave upward on I.
89. (a) If f and t are positive, increasing, concave upward
functions on an interval I, show that the product function f t is concave upward on I.
(b) Show that part (a) remains true if f and t are both
decreasing.
(c) Suppose f is increasing and t is decreasing. Show, by
giving three examples, that f t may be concave upward,
concave downward, or linear. Why doesn’t the argument in parts (a) and (b) work in this case?
90. Suppose f and t are both concave upward on s2`, `d.
Under what condition on f will the composite function
hsxd − f s tsxdd be concave upward?
91. Show that a cubic function (a third-degree polynomial)
always has exactly one point of inflection. If its graph has
three x-intercepts x 1 , x 2 , and x 3 , show that the x-coordinate
of the inflection point is sx 1 1 x 2 1 x 3 dy3.
; 92. For what values of c does the polynomial
Psxd − x 4 1 cx 3 1 x 2 have two inflection points? One
inflection point? None? Illustrate by graphing P for several
values of c. How does the graph change as c decreases?
f sxd − e2x ys2& d
93. Prove that if sc, f scdd is a point of inflection of the graph
of f and f 0 exists in an open interval that contains c, then
f 0scd − 0. [Hint: Apply the First Derivative Test and
Fermat’s Theorem to the function t − f 9.]
(a) Find the asymptote, maximum value, and inflection
points of f .
94. Show that if f sxd − x 4, then f 0s0d − 0, but s0, 0d is not an
inflection point of the graph of f .
2
2
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SECTION 4.4
| |
95. Show that the function tsxd − x x has an inflection point at
s0, 0d but t0s0d does not exist.
96. Suppose that f 09 is continuous and f 9scd − f 0scd − 0, but
f -scd . 0. Does f have a local maximum or minimum
at c ? Does f have a point of inflection at c?
99. The three cases in the First Derivative Test cover the situations commonly encountered but do not exhaust all possibilities. Consider the functions f, t, and h whose values at 0 are
all 0 and, for x ± 0,
f sxd − x 4 sin
97. Suppose f is differentiable on an interval I and f 9sxd . 0 for
all numbers x in I except for a single number c. Prove that f
is increasing on the entire interval I.
1
x
S
D
tsxd − x 4 2 1 sin
S
hsxd − x 4 22 1 sin
1
x
D
1
x
(a) Show that 0 is a critical number of all three functions but
their derivatives change sign infinitely often on both sides
of 0.
(b) Show that f has neither a local maximum nor a local
minimum at 0, t has a local minimum, and h has a local
maximum.
98. For what values of c is the function
f sxd − cx 1
309
Indeterminate Forms and l’Hospital’s Rule
1
x2 1 3
increasing on s2`, `d?
4.4 Indeterminate Forms and l’Hospital’s Rule
Suppose we are trying to analyze the behavior of the function
Fsxd −
ln x
x21
Although F is not defined when x − 1, we need to know how F behaves near 1. In particular, we would like to know the value of the limit
1
lim
ln x
x l1 x 2 1
In computing this limit we can’t apply Law 5 of limits (the limit of a quotient is the quotient of the limits, see Section 2.3) because the limit of the denominator is 0. In fact,
although the limit in (1) exists, its value is not obvious because both numerator and
denominator approach 0 and 00 is not defined.
■ Indeterminate Forms (Types 00, `
`)
In general, if we have a limit of the form
f sxd
x l a tsxd
lim
where both f sxd l 0 and tsxd l 0 as x l a, then this limit may or may not exist and is
called an indeterminate form of type 00. We met some limits of this type in Chapter 2.
For rational functions, we can cancel common factors:
x2 2 x
xsx 2 1d
x
1
− lim
− lim
−
x l1 x 2 2 1
x l1 sx 1 1dsx 2 1d
x l1 x 1 1
2
lim
In Section 3.3 we used a geometric argument to show that
lim
xl0
sin x
−1
x
But these methods do not work for limits such as (1).
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310
CHAPTER 4
Applications of Differentiation
Another situation in which a limit is not obvious occurs when we look for a horizontal
asymptote of F and need to evaluate the limit
2
ln x
lim
xl` x 2 1
It isn’t obvious how to evaluate this limit because both numerator and denominator
become large as x l `. There is a struggle between numerator and denominator. If the
numerator wins, the limit will be ` (the numerator was increasing significantly faster
than the denominator); if the denominator wins, the answer will be 0. Or there may be
some compromise, in which case the answer will be some finite positive number.
In general, if we have a limit of the form
lim
xla
y
where both f sxd l ` (or 2`) and tsxd l ` (or 2`), then the limit may or may not
exist and is called an indeterminate form of type `
`. We saw in Section 2.6 that this type
of limit can be evaluated for certain functions, including rational functions, by dividing
numerator and denominator by the highest power of x that occurs in the denominator.
For instance,
f
g
0
a
y
f sxd
tsxd
x2 2 1
lim
− lim
x l ` 2x 2 1 1
xl`
x
1
x2
120
1
−
−
1
210
2
21 2
x
12
But this method does not work for limits such as (2).
y=m¡(x-a)
■ L’Hospital’s Rule
We now introduce a systematic method, known as l’Hospital’s Rule, for the evaluation of
indeterminate forms of type 00 or type `
`.
y=m™(x-a)
0
a
x
FIGURE 1
Figure 1 suggests visually why
l’Hospital’s Rule might be true. The
first graph shows two differentiable
functions f and t, each of which
approaches 0 as x l a. If we were
to zoom in toward the point sa, 0d,
the graphs would start to look
almost linear. But if the functions
actually were linear, as in the second graph, then their ratio would be
m1sx 2 ad
m1
−
m2sx 2 ad
m2
which is the ratio of their derivatives. This suggests that
f sxd
f 9sxd
lim
− lim
x l a tsxd
x l a t9sxd
L’Hospital’s Rule Suppose f and t are differentiable and t9sxd ± 0 on an open
interval I that contains a (except possibly at a). Suppose that
lim f sxd − 0
and
lim f sxd − 6`
and
xla
or that
xla
lim tsxd − 0
xla
lim tsxd − 6`
xla
(In other words, we have an indeterminate form of type 00 or ``.) Then
lim
xla
f sxd
f 9sxd
− lim
x l a t9sxd
tsxd
if the limit on the right side exists (or is ` or 2`).
NOTE 1 L’Hospital’s Rule says that the limit of a quotient of functions is equal to the
limit of the quotient of their derivatives, provided that the given conditions are satisfied.
It is especially important to verify the conditions regarding the limits of f and t before
using l’Hospital’s Rule.
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SECTION 4.4
L’Hospital
L’Hospital’s Rule is named after a French
nobleman, the Marquis de l’Hospital
(1661–1704), but was discovered by a
Swiss mathematician, John Bernoulli
(1667–1748). You might sometimes see
l’Hospital spelled as l’Hôpital, but he
spelled his own name l’Hospital, as was
common in the 17th century. See Exercise 85 for the example that the Marquis
used to illustrate his rule. See the project following this section for further
historical details.
Indeterminate Forms and l’Hospital’s Rule
311
NOTE 2 L’Hospital’s Rule is also valid for one-sided limits and for limits at infinity or
negative infinity; that is, “x l a” can be replaced by any of the symbols x l a1, x l a2,
x l `, or x l 2`.
NOTE 3 For the special case in which f sad − tsad − 0, f 9 and t9 are continuous, and
t9sad ± 0, it is easy to see why l’Hospital’s Rule is true. In fact, using the alternative form
of the definition of a derivative (2.7.5), we have
f sxd 2 f sad
x2a
f 9sxd
f 9sad
lim
−
−
x l a t9sxd
t9sad
tsxd 2 tsad
lim
xla
x2a
f sxd 2 f sad
x2a
− lim
x l a tsxd 2 tsad
x2a
f sxd 2 f sad
f sxd
− lim
− lim
x l a tsxd 2 tsad
x l a tsxd
lim
xla
fbecause f sad − tsad − 0g
It is more difficult to prove the general version of l’Hospital’s Rule. See Appendix F.
EXAMPLE 1 Find lim
ln x
xl1 x 2 1
.
SOLUTION Since
lim ln x − ln 1 − 0
x l1
and
lim sx 2 1d − 0
x l1
the limit is an indeterminate form of type 00 , so we can apply l’Hospital’s Rule:
Notice that when using
l’Hospital’s Rule we differentiate the
numerator and denominator separately. We do not use the Quotient
Rule.
The graph of the function of Example 2
is shown in Figure 2. We have noticed
previously that exponential functions
grow far more rapidly than power functions, so the result of Example 2 is not
unexpected. See also Exercise 75.
20
y=
0
FIGURE 2
´
≈
d
sln xd
ln x
dx
1yx
lim
− lim
− lim
xl1 x 2 1
xl1 d
xl1 1
sx 2 1d
dx
1
− lim − 1
xl1 x
n
ex
.
xl` x2
EXAMPLE 2 Calculate lim
SOLUTION We have lim x l ` e x − ` and lim x l ` x 2 − `, so the limit is an indeterminate form of type `
` , and l’Hospital’s Rule gives
d
se x d
ex
dx
ex
− lim
lim 2 − lim
xl` x
xl` d
x l ` 2x
sx 2 d
dx
Since e x l ` and 2x l ` as x l `, the limit on the right side is also indeterminate.
A second application of l’Hospital’s Rule gives
10
ex
ex
ex
−
lim
−
lim
−`
xl` x2
x l ` 2x
xl` 2
lim
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n
312
CHAPTER 4
Applications of Differentiation
The graph of the function of Example 3
is shown in Figure 3. We have discussed previously the slow growth of
logarithms, so it isn’t surprising that
this ratio approaches 0 as x l `. See
also Exercise 76.
2
EXAMPLE 3 Calculate lim
ln x
xl`
sx
.
SOLUTION Since ln x l ` and sx l ` as x l `, l’Hospital’s Rule applies:
1yx
1yx
− lim 1 21y2 − lim
x l ` sx
xl` x
xl ` 1y(2sx )
2
lim
ln x
Notice that the limit on the right side is now indeterminate of type 00. But instead of
applying l’Hospital’s Rule a second time as we did in Example 2, we simplify the
expression and see that a second application is unnecessary:
y= ln x
œ„
x
0
10,000
lim
xl`
_1
ln x
sx
− lim
1yx
(
x l ` 1y 2sx
)
− lim
2
x l ` sx
−0
n
In both Examples 2 and 3 we evaluated limits of type `
` , but we got two different
results. In Example 2, the infinite limit tells us that the numerator e x increases significantly faster than the denominator x 2, resulting in larger and larger ratios. In fact, y − e x
grows more quickly than all the power functions y − x n (see Exercise 75). In Example 3
we have the opposite situation; the limit of 0 means that the denominator outpaces the
numerator, and the ratio eventually approaches 0.
FIGURE 3
tan x 2 x
. (See Exercise 2.2.48.)
xl0
x3
EXAMPLE 4 Find lim
SOLUTION Noting that both tan x 2 x l 0 and x 3 l 0 as x l 0, we use l’Hospital’s
Rule:
tan x 2 x
sec2x 2 1
−
lim
xl0
xl0
x3
3x 2
lim
Since the limit on the right side is still indeterminate of type 00, we apply l’Hospital’s
Rule again:
The graph in Figure 4 gives visual confirmation of the result of Example 4. If
we were to zoom in too far, however, we would get an inaccurate
graph because tan x is close to x when
x is small. See Exercise 2.2.48(d).
1
0
FIGURE 4
Because lim x l 0 sec2 x − 1, we simplify the calculation by writing
2 sec2x tan x
1
tan x
1
tan x
− lim sec2 x ! lim
− lim
xl0
x
l
0
x
l
0
xl
0
6x
3
x
3
x
lim
We can evaluate this last limit either by using l’Hospital’s Rule a third time or by
writing tan x as ssin xdyscos xd and making use of our knowledge of trigonometric
limits. Putting together all the steps, we get
y=
_1
sec2x 2 1
2 sec2x tan x
−
lim
xl0
xl0
3x 2
6x
lim
tan x- x
˛
tan x 2 x
sec 2 x 2 1
2 sec 2 x tan x
− lim
− lim
3
2
xl0
xl0
xl0
x
3x
6x
lim
1
−
1
tan x
1
sec 2 x
1
lim
− lim
−
3 xl0 x
3 xl0 1
3
n
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SECTION 4.4
EXAMPLE 5 Find lim 2
xl!
Indeterminate Forms and l’Hospital’s Rule
313
sin x
.
1 2 cos x
SOLUTION If we blindly attempted to use l’Hospital’s Rule, we might think that an
equivalent limit is
cos x
lim
− 2`
x l! 2 sin x
This is wrong! Although the numerator sin x l 0 as x l ! 2, notice that the denominator s1 2 cos xd does not approach 0, so l’Hospital’s Rule can’t be applied here.
The required limit can, in fact, be found by direct substitution because the function
is continuous at ! and the denominator is nonzero there:
lim
x l !2
sin x
sin !
0
−
−
−0
1 2 cos x
1 2 cos !
1 2 s21d
n
Example 5 shows what can go wrong if you use l’Hospital’s Rule without thinking. Some limits can be found using l’Hospital’s Rule but are more easily found by other
methods. (See Examples 2.3.3, 2.3.5, and 2.6.3, and the discussion at the beginning of
this section.) When evaluating any limit, you should consider other methods before using
l’Hospital’s Rule.
■ Indeterminate Products (Type 0 ?`)
If lim x l a f sxd − 0 and lim x l a tsxd − ` (or 2`), then it isn’t clear what the value of
lim x l a f f sxd tsxdg, if any, will be. There is a struggle between f and t. If f wins, the
answer will be 0; if t wins, the answer will be ` (or 2`). Or there may be a compromise
where the answer is a finite nonzero number. For instance,
lim1 x 2 − 0,
lim1
xl0
1
− ` and
x
lim1 x − 0,
lim1
1
− ` and
x2
lim1
1
− ` and
x
xl0
xl0
xl0
lim1 x − 0,
xl0
Figure 5 shows the graph of the
function in Example 6. Notice that
the function is undefined at x − 0 ;
the graph approaches the origin but
never quite reaches it.
xl0
lim1 x 2 ?
1
− lim1 x − 0
xl0
x
lim1 x ?
1
1
−`
2 − xlim
1
l0 x
x
lim1 x ?
1
− lim11 − 1
xl0
x
xl0
xl0
xl0
This kind of limit is called an indeterminate form of type 0 ! `. We can deal with it by
writing the product ft as a quotient:
ft −
f
1yt
or
ft −
t
1yf
This converts the given limit into an indeterminate form of type 00 or `
` so that we can use
l’Hospital’s Rule.
y
y=x ln x
EXAMPLE 6 Evaluate lim1 x ln x.
x l0
0
1
FIGURE 5
x
SOLUTION The given limit is indeterminate because, as x l 0 1, the first factor sxd
approaches 0 while the second factor sln xd approaches 2`. Writing x − 1ys1yxd, we
have 1yx l ` as x l 0 1, so l’Hospital’s Rule gives
lim x ln x − lim1
x l 01
xl0
ln x
1yx
− lim1
− lim1 s2xd − 0
x l 0 21yx 2
xl0
1yx
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n
314
CHAPTER 4
Applications of Differentiation
NOTE In solving Example 6 another possible option would have been to write
lim1 x ln x − lim1
xl0
xl0
x
1yln x
This gives an indeterminate form of the type 00, but if we apply l’Hospital’s Rule we get
a more complicated expression than the one we started with. In general, when we rewrite
an indeterminate product, we try to choose the option that leads to the simpler limit.
■ Indeterminate Differences (Type ` 2 `)
If lim x l a f sxd − ` and lim x l a tsxd − `, then the limit
lim f f sxd 2 tsxdg
xla
is called an indeterminate form of type `2`. Again there is a contest between f
and t. Will the answer be ` ( f wins) or will it be 2` ( t wins) or will they compromise
on a finite number? To find out, we try to convert the difference into a quotient (for
instance, by using a common denominator, or rationalization, or factoring out a common
factor) so that we have an indeterminate form of type 00 or `
`.
EXAMPLE 7 Compute lim1
x l1
S
D
1
1
2
.
ln x
x21
SOLUTION First notice that 1ysln xd l ` and 1ysx 2 1d l ` as x l 11, so the limit
is indeterminate of type `2 `. Here we can start with a common denominator:
lim
x l11
S
1
1
2
ln x
x21
D
− lim1
x l1
x 2 1 2 ln x
sx 2 1d ln x
Both numerator and denominator have a limit of 0, so l’Hospital’s Rule applies, giving
x 2 1 2 ln x
lim1
− lim1
x l1
x l1
sx 2 1d ln x
1
x
x21
− lim1
x l1 x 2 1 1 x ln x
1
sx 2 1d ! 1 ln x
x
12
Again we have an indeterminate limit of type 00, so we apply l’Hospital’s Rule a second
time:
x21
lim
x l11 x 2 1 1 x ln x
− lim1
x l1
− lim1
x l1
1
1
1 1 x ! 1 ln x
x
1
1
−
2 1 ln x
2
n
EXAMPLE 8 Calculate lim se x 2 xd.
xl`
SOLUTION This is an indeterminate difference because both e x and x approach infinity.
We would expect the limit to be infinity because e x l ` much faster than x. But we can
verify this by factoring out x:
ex 2 x − x
S D
ex
21
x
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SECTION 4.4
Indeterminate Forms and l’Hospital’s Rule
315
The term e xyx l ` as x l ` by l’Hospital’s Rule and so we now have a product in
which both factors grow large:
F S DG
lim se x 2 xd − lim x
xl`
xl`
ex
21
x
−`
n
■ Indeterminate Powers (Types 00, `0, 1`)
Several indeterminate forms arise from the limit
lim f f sxdg tsxd
x la
1. lim f sxd − 0
and
2. lim f sxd − `
and
3. lim f sxd − 1
and
xla
xla
xla
Although forms of the type 0 0, `0, and
1` are indeterminate, the form 0 ` is
not indeterminate. (See Exercise 88.)
lim tsxd − 0
type 0 0
lim tsxd − 0
type ` 0
lim tsxd − 6`
type 1`
xla
xla
xla
Each of these three cases can be treated either by taking the natural logarithm:
y − f f sxdg tsxd,
let
then ln y − tsxd ln f sxd
or by using Formula 1.5.10 to write the function as an exponential:
f f sxdg tsxd − e tsxd ln f sxd
(Recall that both of these methods were used in differentiating such functions.) In either
method we are led to the indeterminate product tsxd ln f sxd, which is of type 0 ! `.
EXAMPLE 9 Calculate lim1 s1 1 sin 4xdcot x.
xl0
SOLUTION First notice that as x l 0 1, we have 1 1 sin 4x l 1 and cot x l `, so the
given limit is indeterminate (type 1` ). Let
y − s1 1 sin 4xdcot x
Then
ln y − ln fs1 1 sin 4xdcot x g − cot x ln s1 1 sin 4xd −
ln s1 1 sin 4xd
tan x
so l’Hospital’s Rule gives
The graph of the function y − x x,
x . 0, is shown in Figure 6. Notice
that although 0 0 is not defined, the
values of the function approach 1
as x l 01. This confirms the result
of Example 10.
2
4 cos 4x
ln s1 1 sin 4xd
1 1 sin 4x
lim ln y − lim1
− lim1
−4
x l 01
xl 0
xl0
tan x
sec2x
So far we have computed the limit of ln y, but what we want is the limit of y. To find
this we use the fact that y − e ln y:
lim s1 1 sin 4xdcot x − lim1 y − lim1 e ln y − e 4
x l 01
xl0
xl0
n
EXAMPLE 10 Find lim1 x x.
xl0
_1
FIGURE 6
0
2
SOLUTION Notice that this limit is indeterminate since 0 x − 0 for any x . 0 but
x 0 − 1 for any x ± 0. (Recall that 0 0 is undefined.) We could proceed as in Example 9
or by writing the function as an exponential:
x x − se ln x d x − e x ln x
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316
CHAPTER 4
Applications of Differentiation
In Example 6 we used l’Hospital’s Rule to show that
lim x ln x − 0
x l 01
lim x x − lim1 e x ln x − e 0 − 1
Therefore
x l 01
Exercises
4.4
1–4 Given that
lim tsxd − 0
lim f sxd − 0
xla
xla
lim psxd − `
xla
7. The graph of a function f and its tangent line at 0 are shown.
f sxd
What is the value of lim x
?
xl0 e 2 1
lim hsxd − 1
xla
lim qs xd − `
xla
y
which of the following limits are indeterminate forms? For
any limit that is not an indeterminate form, evaluate it where
possible.
f sxd
x l a tsxd
hsxd
(d) lim
xla
psxd
f sxd
8–70 Find the limit. Use l’Hospital’s Rule where appropriate.
If there is a more elementary method, consider using it. If
l’Hospital’s Rule doesn’t apply, explain why.
psxd
(e) lim
x l a qsxd
2. (a) lim f f sxdpsxdg
(b) lim fhsxdpsxdg
xla
xl3 x2 2 9
(c) lim f psxdqsxdg
xla
9. lim
x l4
(b) lim f psxd 2 qsxdg
xla
xla
x7 2 1
x l1 x 3 2 1
xla
4. (a) lim f f sxdg tsxd
(b) lim f f sxdg psxd
13.
xla
xl a
(c) lim fhsxdg psxd
(d) lim f psxdg f sxd
(e) lim f psxdg
(f ) lim spsxd
xla
xla
xla
5–6 Use the graphs of f and t and their tangent lines at s2, 0d to
f sxd
find lim
.
x l 2 tsxd
6.
y
y=1.5(x-2)
0
2
4
x
y=5 (x-2)
0
2
sin sx 2 1d
xl1 x 3 1 x 2 2
y=2-x
lim
x3 1 8
x12
12. lim
sx 2 2
x24
10.
x l 22
x l4
14. lim
x2
x l 0 1 2 cos x
16. lim
18. lim
21. lim1
ln x
x
22. lim
ln sxy3d
xl3 3 2 x
24. lim
s1 1 2x 2 s1 2 4x
xl0
x
26. lim
e x 1 e2x 2 2
xl0 ex 2 x 2 1
28. lim
25. lim
27. lim
1 1 cos "
" l ! 1 2 cos "
sx
xl` 1 1 e x
tan 3x
x l 0 sin 2x
19. lim
23. lim
x
g
17. lim
xl0
f
g
sin x 2 cos x
tan x 2 1
e 2t 2 1
tl0
sin t
xla
f
lim
x l !y4
15. lim
qsxd
qsxd
y=1.8(x-2)
x 2 2 2x 2 8
x24
11. lim
(c) lim f psxd 1 qsxdg
5. y
x23
8. lim
xla
3. (a) lim f f sxd 2 psxdg
x
0
(b) lim
x l a psxd
y=x
y=ƒ
f sxd
x l a psxd
1. (a) lim
(c) lim
n
xl0
20. lim
x 1 x2
x l ` 1 2 2x 2
xl`
ln sx
x2
8t 2 5t
tl0
t
e uy10
ul ` u 3
xl0
sinh x 2 x
x3
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SECTION 4.4
29. lim
tanh x
tan x
30. lim
31. lim
sin21x
x
32. lim
x3x
xl0 3 2 1
34. lim
lns1 1 xd
x l 0 cos x 1 e x 2 1
36. lim
arctan 2x
ln x
38. lim
39. lim
xa 2 1
, b±0
xl1 xb 2 1
40. lim
cos x 2 1 1 12 x 2
41. lim
xl0
x4
x 2 sin x
42. lim
x l 0 x sinsx 2 d
43. lim x sins!yxd
44. lim sx e2xy2
45. lim sin 5x csc 3x
46.
xl0
xl0
33. lim
35. lim
37. lim1
xl0
2
74. f sxd − 2x sin x,
tsxd − sec x 2 1
x sinsx 2 1d
x l 1 2x 2 2 x 2 1
75. Prove that
for any positive integer n. This shows that the exponential
function approaches infinity faster than any power of x.
e2x
x l ` s!y2d 2 tan21x
D
D
50.
S D
54. lim1
55. lim1
1
1
2
x
tan x
xl0
xl0
S
1
1
2
x
tan21 x
xl`
57. lim1 x sx
58. lim1 stan 2xd x
59. lim s1 2 2xd1yx
60. lim
61. lim1 x 1ys12xd
62. lim se x 1 10xd1yx
xl0
xl0
xl`
x l1
63. lim x
64. lim x e
a
x
bx
2x
xl`
65. lim1 s4x 1 1d cot x
66. lim1 s1 2 cos xd sin x
x l0
67. lim1 s1 1 sin 3xd
x l0
1yx
xl0
68. lim scos xd1yx
xl0
x
x l0
S D
11
xl`
1yx
xl`
69. lim1
D
56. lim sx 2 ln xd
x l0
x 21
ln x 1 x 2 1
x
sx 2 1 1
78.
70. lim
xl`
S
; 79. Investigate the family of curves f sxd − e 2 cx. In particular, find the limits as x l 6` and determine the
values of c for which f has an absolute minimum. What
happens to the minimum points as c increases?
2
2x 2 3
2x 1 5
D
2x11
80. If an object with mass m is dropped from rest, one model
for its speed v after t seconds, taking air resistance into
account, is
mt
v−
s1 2 e 2ctym d
c
where t is the acceleration due to gravity and c is a positive
constant. (In Chapter 9 we will be able to deduce this equation from the assumption that the air resistance is proportional to the speed of the object; c is the proportionality
constant.)
(a) Calculate lim t l ` v. What is the meaning of this limit?
(b) For fixed t, use l’Hospital’s Rule to calculate lim cl 01 v.
What can you conclude about the velocity of a falling
object in a vacuum?
81. If an initial amount A0 of money is invested at an interest
rate r compounded n times a year, the value of the investment after t years is
S D
A − A0 1 1
; 71–72 Use a graph to estimate the value of the limit. Then use
l’Hospital’s Rule to find the exact value.
71. lim
xl`
S D
11
2
x
sec x
lim
x l s!y2d2 tan x
x
1
1
2 x
x
e 21
xl0
xl `
lim cos x sec 5x
53. lim1
x l0
77. lim
x l s!y2d2
52. lim scsc x 2 cot xd
xl1
ln x
−0
xp
77–78 What happens if you try to use l’Hospital’s Rule to find
the limit? Evaluate the limit using another method.
1
x
x
1
2
x21
ln x
51. lim
lim
for any number p . 0. This shows that the logarithmic function approaches infinity more slowly than any power of x.
xl`
49. lim1 ln x tans! xy2d
76. Prove that
xl`
lim x ln 1 2
x l 2`
ex
−`
xl` xn
lim
48. lim x 3y2 sins1yxd
xl`
S
S
e x 1 e2x 2 2 cos x
xl0
x sin x
xl`
xl0
x l1
tsxd − x 3 1 4x
x 2 sin x
x l 0 sin x 2 x
xl`
47. lim x 3e 2x
sln xd2
x
73. f sxd − e x 2 1,
xl`
317
; 73–74 Illustrate l’Hospital’s Rule by graphing both f sxdytsxd
and f 9sxdyt9sxd near x − 0 to see that these ratios have the same
limit as x l 0. Also, calculate the exact value of the limit.
x 2 sin x
x l 0 x 2 tan x
x
Indeterminate Forms and l’Hospital’s Rule
x
x
72. lim
5 24
x
x l 0 3x 2 2x
r
n
nt
If we let n l `, we refer to the continuous compounding of
interest. Use l’Hospital’s Rule to show that if interest is
compounded continuously, then the amount after t years is
A − A0 e rt
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318
CHAPTER 4
Applications of Differentiation
82. Light enters the eye through the pupil and strikes the retina,
where photoreceptor cells sense light and color. W. Stanley
Stiles and B. H. Crawford studied the phenomenon in which
measured brightness decreases as light enters farther from
the center of the pupil (see the figure).
B
A
A light beam A that enters through the center of the pupil
measures brighter than a beam B entering near the edge of
the pupil.
They detailed their findings of this phenomenon, known as
the Stiles– Crawford effect of the first kind, in an important
paper published in 1933. In particular, they observed that the
amount of luminance sensed was not proportional to the area
of the pupil as they expected. The percentage P of the total
luminance entering a pupil of radius r mm that is sensed at
the retina can be described by
the carrying capacity and represents the maximum population
size that can be supported, and
A−
84. A metal cable has radius r and is covered by insulation so that
the distance from the center of the cable to the exterior of the
insulation is R. The velocity v of an electrical impulse in the
cable is
r 2
r
v − 2c
ln
R
R
SD SD
where c is a positive constant. Find the following limits and
interpret your answers.
(a) lim1 v
(b) lim1 v
R lr
r l0
85. The first appearance in print of l’Hospital’s Rule was in the
book Analyse des infiniment petits published by the Marquis
de l’Hospital in 1696. This was the first calculus textbook
ever published. The example that the Marquis used in that
book to illustrate his rule was to find the limit of the function
3
aax
s2a 3x 2 x 4 2 a s
4
a2s
ax 3
2
where ' is an experimentally determined constant, typically
about 0.05.
(a) What is the percentage of luminance sensed by a pupil of
radius 3 mm? Use ' − 0.05.
(b) Compute the percentage of luminance sensed by a pupil
of radius 2 mm. Does it make sense that it is larger than
the answer to part (a)?
(c) Compute lim1 P. Is the result what you would expect?
P0
where P0 is the initial population.
(a) Compute lim tl ` Pstd. Explain why your answer is to be
expected.
(b) Compute lim Ml ` Pstd. (Note that A is defined in terms
of M.) What kind of function is your result?
y−
1 2 102'r
P−
'r 2 ln 10
M 2 P0
as x approaches a, where a . 0. (At that time it was common
to write aa instead of a 2.) Solve this problem.
86. The figure shows a sector of a circle with central angle ". Let
As"d be the area of the segment between the chord PR and
the arc PR. Let Bs"d be the area of the triangle PQR. Find
lim " l 01 As"dyBs"d.
P
A(¨)
rl0
Is this result physically possible?
Source: Adapted from W. Stiles and B. Crawford, “The Luminous Efficiency
of Rays Entering the Eye Pupil at Different Points.” Proceedings of the Royal
Society of London, Series B: Biological Sciences 112 (1933): 428–50.
83. Logistic Equations Some populations initally grow exponentially but eventually level off. Equations of the form
O
87. Evaluate
M
1 1 Ae 2kt
where M, A, and k are positive constants, are called logistic
equations and are often used to model such populations. (We
will investigate these in detail in Chapter 9.) Here M is called
F
B(¨ )
R
Q
S DG
lim x 2 x 2 ln
xl`
Pstd −
¨
11x
x
88. Suppose f is a positive function. If lim xl a f sxd − 0 and
lim xl a tsxd − `, show that
lim f f sxdg tsxd − 0
xla
This shows that 0 ` is not an indeterminate form.
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WRITING PROJECT
89. Find functions f and t where lim f sxd − lim tsxd − ` and
xl0
(a) lim
f sxd
x l 0 tsxd
xl0
(b) lim f f sxd 2 tsxdg − 7
−7
xl0
90. For what values of a and b is the following equation true?
lim
xl0
S
sin 2x
b
1a1 2
x3
x
91. Let
f sxd −
H
e21yx
0
2
D
−0
if x ± 0
if x − 0
(a) Use the definition of derivative to compute f 9s0d.
Thomas Fisher Rare Book Library
WRITING PROJECT
www.StewartCalculus.com
The Internet is another source of
information for this project. Click on
History of Mathematics for a list of
reliable websites.
The Origins of l’Hospital’s Rule
319
(b) Show that f has derivatives of all orders that are
defined on R. [Hint: First show by induction that there
is a polynomial pnsxd and a nonnegative integer k n such
that f sndsxd − pnsxdf sxdyx k n for x ± 0.]
; 92. Let
f sxd −
H| |
x x if x ± 0
1
if x − 0
(a) Show that f is continuous at 0.
(b) Investigate graphically whether f is differentiable at 0
by zooming in several times toward the point s0, 1d on the
graph of f .
(c) Show that f is not differentiable at 0. How can you
reconcile this fact with the appearance of the graphs in
part (b)?
THE ORIGINS OF L’HOSPITAL’S RULE
L’Hospital’s Rule was first published in 1696 in the Marquis de l’Hospital’s calculus textbook Analyse des infiniment petits, but the rule was discovered in 1694 by the Swiss mathematician John (Johann) Bernoulli. The explanation is that these two mathematicians had
entered into a curious business arrangement whereby the Marquis de l’Hospital bought
the rights to Bernoulli’s mathematical discoveries. The details, including a translation of
l’Hospital’s letter to Bernoulli proposing the arrangement, can be found in the book by
Eves [1].
Write an essay on the historical and mathematical origins of l’Hospital’s Rule. Start by
providing brief biographical details of both men (the dictionary edited by Gillispie [2] is a
good source) and outline the business deal between them. Then give l’Hospital’s statement of
his rule, which is found in Struik’s source book [4] and more briefly in the book of Katz [3].
Notice that l’Hospital and Bernoulli formulated the rule geometrically and gave the answer in
terms of differentials. Compare their statement with the version of l’Hospital’s Rule given in
Section 4.4 and show that the two statements are essentially the same.
1. Howard W. Eves, Mathematical Circles: Volume 1 (Washington, D.C.: Mathematical
Association of America, 2003). First published 1969 as In Mathematical Circles (Volume 2: Quadrants III and IV) by Prindle Weber and Schmidt.
2. C. C. Gillispie, ed., Dictionary of Scientific Biography, 8 vols. (New York: Scribner,
1981). See the article on Johann Bernoulli by E. A. Fellmann and J. O. Fleckstein
in Volume II and the article on the Marquis de l’Hospital by Abraham Robinson in
Volume III.
3. Victor J. Katz, A History of Mathematics: An Introduction. 3rd ed. (New York: Pearson,
2018).
4. Dirk Jan Stuik, ed. A Source Book in Mathematics, 1200 –1800 (1969; repr., Princeton, NJ:
Princeton University Press, 2016).
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320
CHAPTER 4
Applications of Differentiation
4.5 Summary of Curve Sketching
30
y=8˛-21≈+18x+2
_2
4
_10
FIGURE 1
8
0
y=8˛-21≈+18x+2
6
2
FIGURE 2
So far we have been concerned with some particular aspects of curve sketching: domain,
range, and symmetry in Chapter 1; limits, continuity, and asymptotes in Chapter 2; derivatives and tangents in Chapters 2 and 3; and extreme values, intervals of increase and
decrease, concavity, points of inflection, and l’Hospital’s Rule in this chapter. It is now
time to put all of this information together to sketch graphs that reveal the important
features of functions.
You might ask: Why don’t we just use a graphing calculator or computer to graph a
curve? Why do we need to use calculus?
It’s true that technology is capable of producing very accurate graphs. But even the
best graphing devices have to be used intelligently. It is easy to arrive at a misleading
graph, or to miss important details of a curve, when relying solely on technology. (See
the topic Graphing Calculators and Computers at www.StewartCalculus.com, especially
Examples 1, 3, 4, and 5. See also Section 4.6.) The use of calculus enables us to discover
the most interesting aspects of graphs and in many cases to calculate maximum and
minimum points and inflection points exactly instead of approximately.
For instance, Figure 1 shows the graph of f sxd − 8x 3 2 21x 2 1 18x 1 2. At first
glance it seems reasonable: It has the same shape as cubic curves like y − x 3, and it
appears to have no maximum or minimum point. But if you compute the derivative, you
will see that there is a maximum when x − 0.75 and a minimum when x − 1. Indeed,
if we zoom in to this portion of the graph, we see that behavior exhibited in Figure 2.
Without calculus, we could easily have overlooked it.
In the next section we will graph functions by using the interaction between calculus
and technology. In this section we draw graphs (by hand) by first considering the following information. A graph produced by a calculator or computer can serve as a check on
your work.
■ Guidelines for Sketching a Curve
The following checklist is intended as a guide to sketching a curve y − f sxd by hand. Not
every item is relevant to every function. (For instance, a given curve might not have an
asymptote or possess symmetry.) But the guidelines provide all the information you need
to make a sketch that displays the most important aspects of the function.
A. Domain It’s often useful to start by determining the domain D of f , that is, the set
of values of x for which f sxd is defined.
y
0
x
(a) Even function: reflectional symmetry
y
0
(b) Odd function: rotational symmetry
FIGURE 3
x
B. Intercepts The y-intercept is f s0d and this tells us where the curve intersects the
y-axis. To find the x-intercepts, we set y − 0 and solve for x. (You can omit this
step if the equation is difficult to solve.)
C. Symmetry
(i) If f s2xd − f sxd for all x in D, that is, the equation of the curve is unchanged
when x is replaced by 2x, then f is an even function and the curve is symmetric about
the y-axis. (See Section 1.1.) This means that our work is cut in half. If we know what
the curve looks like for x > 0, then we need only reflect about the y-axis to obtain the
complete curve [see Figure 3(a)]. Here are some examples: y − x 2, y − x 4, y − x ,
and y − cos x.
(ii) If f s2xd − 2f sxd for all x in D, then f is an odd function and the curve
is symmetric about the origin. Again we can obtain the complete curve if we know
what it looks like for x > 0. [Rotate 180° about the origin; see Figure 3(b).] Some
simple examples of odd functions are y − x, y − x 3, y − 1yx, and y − sin x.
| |
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SECTION 4.5
321
Summary of Curve Sketching
(iii) If f sx 1 pd − f sxd for all x in D, where p is a positive constant, then f is a
periodic function and the smallest such number p is called the period. For instance,
y − sin x has period 2! and y − tan x has period !. If we know what the graph looks
like in an interval of length p, then we can use translation to visualize the entire graph
(see Figure 4).
y
period p
FIGURE 4
Periodic function:
translational symmetry
a-p
0
a
a+p
a+2p
x
D. Asymptotes
(i) Horizontal Asymptotes. Recall from Section 2.6 that if either lim x l ` f sxd − L
or lim x l2 ` f sxd − L, then the line y − L is a horizontal asymptote of the curve
y − f sxd. If it turns out that lim x l ` f sxd − ` (or 2`), then we do not have an
asymptote to the right, but this fact is still useful information for sketching the curve.
(ii) Vertical Asymptotes. Recall from Section 2.2 that the line x − a is a vertical
asymptote if at least one of the following statements is true:
1
lim f sxd − `
x l a1
lim f sxd − 2`
x l a1
lim f sxd − `
x l a2
lim f sxd − 2`
x l a2
(For rational functions you can locate the vertical asymptotes by equating the denominator to 0 after canceling any common factors. But for other functions this method
does not apply.) Furthermore, in sketching the curve it is useful to know exactly
which of the statements in (1) is true. If f sad is not defined but a is an endpoint of the
domain of f, then you should compute lim xl a f sxd or lim xl a f sxd, whether or not
this limit is infinite.
(iii) Slant Asymptotes. These are discussed at the end of this section.
2
1
E. Intervals of Increase or Decrease Use the I/D Test. Compute f 9sxd and find the
intervals on which f 9sxd is positive ( f is increasing) and the intervals on which f 9sxd
is negative ( f is decreasing).
F. Local Maximum or Minimum Values Find the critical numbers of f [the numbers c where f 9scd − 0 or f 9scd does not exist]. Then use the First Derivative Test. If
f 9 changes from positive to negative at a critical number c, then f scd is a local maximum. If f 9 changes from negative to positive at c, then f scd is a local minimum.
Although it is usually preferable to use the First Derivative Test, you can use the
Second Derivative Test if f 9scd − 0 and f 0scd ± 0. Then f 0scd . 0 implies that
f scd is a local minimum, whereas f 0scd , 0 implies that f scd is a local maximum.
G. Concavity and Points of Inflection Compute f 0sxd and use the Concavity Test.
The curve is concave upward where f 0sxd . 0 and concave downward where
f 0sxd , 0. Inflection points occur where the direction of concavity changes.
H. Sketch the Curve Using the information in items A– G, draw the graph. Sketch the
asymptotes as dashed lines. Plot the intercepts, maximum and minimum points, and
inflection points. Then make the curve pass through these points, rising and falling
according to E, with concavity according to G, and approaching the asymptotes.
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322
CHAPTER 4
Applications of Differentiation
If additional accuracy is desired near any point, you can compute the value of the
derivative there. The tangent indicates the direction in which the curve proceeds.
EXAMPLE 1 Use the guidelines to sketch the curve y −
A. Domain The domain is
hx
2x 2
.
x2 2 1
| x 2 1 ± 0j − hx | x ± 61j − s2`, 21d ø s21, 1d ø s1, `d
2
B. Intercepts The x- and y-intercepts are both 0.
C. Symmetry Since f s2xd − f sxd, the function f is even. The curve is symmetric
about the y-axis.
2x 2
2
D. Asymptotes
lim 2
− lim
−2
x l6` x 2 1
x l6` 1 2 1yx 2
Therefore the line y − 2 is a horizontal asymptote (at both the left and right).
Since the denominator is 0 when x − 61, we compute the following limits:
y
lim1
x l1
y=2
2x 2
−`
x2 2 1
lim2
2x 2
− 2`
x 21
lim 2
2x 2
−`
x2 2 1
x l1
2
0
x=_1
x
lim 1
x l 21
2x
− 2`
2
x 21
x l 21
2
Therefore the lines x − 1 and x − 21 are vertical asymptotes. This information
about limits and asymptotes enables us to draw the preliminary sketch in Figure 5,
showing the parts of the curve near the asymptotes.
x=1
FIGURE 5
E. Intervals of Increase or Decrease
Preliminary sketch
We have shown the curve approaching its horizontal asymptote from
above in Figure 5. This is confirmed by
the intervals of increase and decrease.
f 9sxd −
sx 2 2 1ds4xd 2 2x 2 ! 2x
24x
− 2
2
2
sx 2 1d
sx 2 1d2
Since f 9sxd . 0 when x , 0 sx ± 21d and f 9sxd , 0 when x . 0 sx ± 1d, f is
increasing on s2`, 21d and s21, 0d and decreasing on s0, 1d and s1, `d.
F. Local Maximum or Minimum Values The only critical number is x − 0. Since f 9
changes from positive to negative at 0, f s0d − 0 is a local maximum by the First
Derivative Test.
y
G. Concavity and Points of Inflection
f 0sxd −
y=2
Since 12x 2 1 4 . 0 for all x, we have
0
x
x=_1
sx 2 2 1d2 s24d 1 4x ! 2sx 2 2 1d2x
12x 2 1 4
−
sx 2 2 1d4
sx 2 2 1d3
x=1
FIGURE 6
Finished sketch of y −
2x 2
x 21
2
f 0sxd . 0 &?
x 2 2 1 . 0 &?
| |
|x| . 1
and f 0sxd , 0 &? x , 1. Thus the curve is concave upward on the intervals
s2`, 21d and s1, `d and concave downward on s21, 1d. It has no point of inflection because 1 and 21 are not in the domain of f.
H. Sketch the Curve Using the information in E – G, we finish the sketch in Figure 6.
EXAMPLE 2 Sketch the graph of f sxd −
A. Domain The domain is hx
x2
sx 1 1
n
.
| x 1 1 . 0j − hx | x . 21j − s21, `d.
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SECTION 4.5
Summary of Curve Sketching
323
B. Intercepts The x- and y-intercepts are both 0.
C. Symmetry None
D. Asymptotes Since
x2
lim
x l ` sx 1 1
−`
there is no horizontal asymptote. Since sx 1 1 l 0 as x l 211 and f sxd is
always positive, we have
lim 1
x l 21
x2
sx 1 1
−`
and so the line x − 21 is a vertical asymptote.
E. Intervals of Increase or Decrease
f 9sxd −
3x 2 1 4x
xs3x 1 4d
sx 1 1 s2xd 2 x 2 ! 1y( 2sx 1 1 )
−
−
x11
2sx 1 1d3y2
2sx 1 1d3y2
We see that f 9sxd − 0 when x − 0 (notice that 243 is not in the domain of f ), so the
only critical number is 0. Since f 9sxd , 0 when 21 , x , 0 and f 9sxd . 0 when
x . 0, f is decreasing on s21, 0d and increasing on s0, `d.
F. Local Maximum or Minimum Values Since f 9s0d − 0 and f 9 changes from negative to positive at 0, f s0d − 0 is a local (and absolute) minimum by the First Derivative Test.
G. Concavity and Points of Inflection
y
f 0sxd −
y=
x=_1
FIGURE 7
0
≈
œ„„„„
x+1
x
2sx 1 1d3y2s6x 1 4d 2 s3x 2 1 4xd3sx 1 1d1y2
3x 2 1 8x 1 8
−
3
4sx 1 1d
4sx 1 1d5y2
Note that the denominator is always positive. The numerator is the quadratic
3x 2 1 8x 1 8, which is always positive because its discriminant is
b 2 2 4ac − 232, which is negative, and the coefficient of x 2 is positive. Thus
f 0sxd . 0 for all x in the domain of f , which means that f is concave upward
on s21, `d and there is no point of inflection.
H. Sketch the Curve The curve is sketched in Figure 7.
EXAMPLE 3 Sketch the graph of f sxd − xe x.
A. Domain The domain is R.
B. Intercepts The x- and y-intercepts are both 0.
C. Symmetry None
D. Asymptotes Because both x and e x become large as x l `, we have
lim x l ` xe x − `. As x l 2`, however, e x l 0 and so we have an indeterminate product that requires the use of l’Hospital’s Rule:
lim xe x − lim
x l2`
x
x l2` e2x
− lim
1
x l2` 2e2x
− lim s2e x d − 0
x l2`
Thus the x-axis is a horizontal asymptote.
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n
324
CHAPTER 4
Applications of Differentiation
E. Intervals of Increase or Decrease
f 9sxd − xe x 1 e x − sx 1 1de x
Since e x is always positive, we see that f 9sxd . 0 when x 1 1 . 0, and f 9sxd , 0
when x 1 1 , 0. So f is increasing on s21, `d and decreasing on s2`, 21d.
y
y=x´
F. Local Maximum or Minimum Values Because f 9s21d − 0 and f 9 changes from
negative to positive at x − 21, f s21d − 2e21 < 20.37 is a local (and
absolute) minimum.
G. Concavity and Points of Inflection
1
_2
_1
(_1, _1/e)
FIGURE 8
f 0sxd − sx 1 1de x 1 e x − sx 1 2de x
x
Since f 0sxd . 0 if x . 22 and f 0sxd , 0 if x , 22, f is concave upward
on s22, `d and concave downward on s2`, 22d. The inflection point is
s22, 22e22 d < s22, 20.27d.
H. Sketch the Curve We use this information to sketch the curve in Figure 8.
EXAMPLE 4 Sketch the graph of f sxd −
A. Domain The domain is R.
n
cos x
.
2 1 sin x
B. Intercepts The y-intercept is f s0d − 12. The x-intercepts occur when cos x − 0, that
is, x − s!y2d 1 n!, where n is an integer.
C. Symmetry f is neither even nor odd, but f sx 1 2!d − f sxd for all x and so
f is periodic and has period 2!. Thus, in what follows, we need to consider only
0 < x < 2! and then extend the curve by translation in part H.
D. Asymptotes None
E. Intervals of Increase or Decrease
f 9sxd −
s2 1 sin xds2sin xd 2 cos x scos xd
2 sin x 1 1
−2
2
s2 1 sin xd
s2 1 sin xd 2
The denominator is always positive, so f 9sxd . 0 when 2 sin x 1 1 , 0 &?
sin x , 221 &? 7!y6 , x , 11!y6. So f is increasing on s7!y6, 11!y6d and
decreasing on s0, 7!y6d and s11!y6, 2!d.
F. Local Maximum or Minimum Values From part E and the First Derivative Test,
we see that the local minimum value is f s7!y6d − 21ys3 and the local maximum
value is f s11!y6d − 1ys3.
G. Concavity and Points of Inflection If we use the Quotient Rule again and simplify, we get
f 0sxd − 2
2 cos x s1 2 sin xd
s2 1 sin xd 3
Because s2 1 sin xd 3 . 0 and 1 2 sin x > 0 for all x, we know that f 0sxd . 0
when cos x , 0, that is, !y2 , x , 3!y2. So f is concave upward on s!y2, 3!y2d
and concave downward on s0, !y2d and s3!y2, 2!d. The inflection points are
s!y2, 0d and s3!y2, 0d.
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SECTION 4.5
325
Summary of Curve Sketching
H. Sketch the Curve The graph of the function restricted to 0 < x < 2! is shown in
Figure 9. Then we extend it, using periodicity, to arrive at the graph in Figure 10.
y
11π
y
1
” 6 , œ„3 ’
1
2
π
π
2
3π
2
1
2
2π x
_π
π
2π
3π
x
1
- ’
” 7π
6 , œ„3
FIGURE 9
FIGURE 10
n
EXAMPLE 5 Sketch the graph of y − lns4 2 x 2 d.
A. Domain The domain is
hx
| 4 2 x . 0j − hx | x , 4j − hx | | x | , 2j − s22, 2d
2
2
B. Intercepts The y-intercept is f s0d − ln 4. To find the x-intercept we set
y − lns4 2 x 2 d − 0
We know that ln 1 − 0, so we have 4 2 x 2 − 1 ? x 2 − 3 and therefore the
x-intercepts are 6s3.
C . Symmetry Since f s2xd − f sxd, f is even and the curve is symmetric about the
y-axis.
D. Asymptotes We look for vertical asymptotes at the endpoints of the domain. Since
4 2 x 2 l 0 1 as x l 2 2 and also as x l 221, we have
lim lns4 2 x 2 d − 2`
x l 22
lim lns4 2 x 2 d − 2`
x l 221
Thus the lines x − 2 and x − 22 are vertical asymptotes.
E . Intervals of Increase or Decrease
f 9sxd −
22x
4 2 x2
Since f 9sxd . 0 when 22 , x , 0 and f 9sxd , 0 when 0 , x , 2, f is increasing
on s22, 0d and decreasing on s0, 2d.
y
(0, ln 4)
x=_2
x=2
{_ œ„3, 0}
FIGURE 11
y − lns4 2 x 2 d
0
{œ„
3, 0}
x
F . Local Maximum or Minimum Values The only critical number is x − 0. Since f 9
changes from positive to negative at 0, f s0d − ln 4 is a local maximum by the First
Derivative Test.
G. Concavity and Points of Inflection
f 0sxd −
s4 2 x 2 ds22d 1 2xs22xd
28 2 2x 2
−
2 2
s4 2 x d
s4 2 x 2 d2
Since f 0sxd , 0 for all x, the curve is concave downward on s22, 2d and has no
inflection point.
H. Sketch the Curve Using this information, we sketch the curve in Figure 11.
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n
326
CHAPTER 4
Applications of Differentiation
■ Slant Asymptotes
y
Some curves have asymptotes that are oblique, that is, neither horizontal nor vertical. If
y=ƒ
lim f f sxd 2 smx 1 bdg − 0
ƒ-(mx+b)
xl`
y=mx+b
0
x
FIGURE 12
where m ± 0, then the line y − mx 1 b is called a slant asymptote because the vertical distance between the curve y − f sxd and the line y − mx 1 b approaches 0, as
in Figure 12. (A similar situation exists if we let x l 2`.) In the case of rational functions, slant asymptotes occur when the degree of the numerator is one more than the
degree of the denominator. In such a case the equation of the slant asymptote can be
found by long division as in the following example.
EXAMPLE 6 Sketch the graph of f sxd −
x3
.
x2 1 1
A. Domain The domain is R.
B. Intercepts The x- and y-intercepts are both 0.
C. Symmetry Since f s2xd − 2f sxd, f is odd and its graph is symmetric about the
origin.
D. Asymptotes Since x 2 1 1 is never 0, there is no vertical asymptote. Since
f sxd l ` as x l ` and f sxd l 2` as x l 2`, there is no horizontal asymptote.
But long division gives
f sxd −
x3
x
−x2 2
2
x 11
x 11
This equation suggests that y − x is a candidate for a slant asymptote. In fact,
f sxd 2 x − 2
x
−2
x2 1 1
1
x
11
1
x2
l 0 as
x l 6`
So the line y − x is indeed a slant asymptote.
E. Intervals of Increase or Decrease
f 9sxd −
sx 2 1 1ds3x 2 d 2 x 3 ! 2x
x 2sx 2 1 3d
−
sx 2 1 1d2
sx 2 1 1d2
Since f 9sxd . 0 for all x (except 0), f is increasing on s2`, `d.
F. Local Maximum or Minimum Values Although f 9s0d − 0, f 9 does not change
sign at 0, so there is no local maximum or minimum.
G. Concavity and Points of Inflection
f 0sxd −
sx 2 1 1d2 s4x 3 1 6xd 2 sx 4 1 3x 2 d ! 2sx 2 1 1d2x
2xs3 2 x 2 d
−
2
4
sx 1 1d
sx 2 1 1d3
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SECTION 4.5
y
y=
Interval
0
3œ„
3
’
4
x , 2s3
2s3 , x , 0
x
3œ„
3
”_ œ„3, _ 4 ’
327
Since f 0sxd − 0 when x − 0 or x − 6s3, we set up the following chart:
˛
≈+1
”œ„3,
Summary of Curve Sketching
0 , x , s3
x . s3
inflection
points
x
3 2 x2
sx 2 1 1d3
f 0sxd
f
2
2
1
1
CU on (2`, 2s3 )
2
1
1
2
1
1
1
1
1
2
1
2
CD on (2s3, 0)
CU on ( 0, s3 )
CD on (s3, `)
The points of inflection are (2s3, 243 s3 ), s0, 0d, and (s3, 34 s3 ).
y=x
FIGURE 13
H. Sketch the Curve The graph of f is sketched in Figure 13.
n
4.5 Exercises
1–54 Use the guidelines of this section to sketch the curve.
3
1. y − x 1 3x
2
3
2. y − 2x 2 12x 1 18x
4
4
3. y − x 2 4x
5. y − xsx 2 4d
7.
2
4. y − x 2 8x 1 8
3
y − 15 x 5 2 83 x 3 1 16x
9. y −
2
2x 1 3
x12
5
x 2 1 5x
25 2 x 2
12. y − 1 1
13. y −
x
x2 2 4
14. y −
1
1
1 2
x
x
1
x2 2 4
sx 2 1d2
16. y − 2
x 11
18. y −
x
x3 2 1
x3
19. y − 3
x 11
x3
20. y −
x22
21. y − sx 2 3dsx
3
22. y − sx 2 4ds
x
23. y − sx 1 x 2 2
24. y − sx 1 x 2 x
25. y −
27. y −
x
sx 1 1
2
s1 2 x 2
x
29. y − x 2 3x
1y3
35. y − x tan x,
2!y2 , x , !y2
37. y − sin x 1 s3 cos x, 22! < x < 2!
x2x
2 2 3x 1 x 2
2
34. y − x 1 cos x
8. y − s4 2 x d
11. y −
x21
x2
33. y − sin3 x
36. y − 2x 2 tan x,
2 5
2
17. y −
3
32. y − s
x3 1 1
6. y − x 2 5x
10. y −
x2
15. y − 2
x 13
3
31. y − s
x2 2 1
2
26. y − x s2 2 x 2
28. y −
x
sx 2 1
2
30. y − x 5y3 2 5x 2y3
2!y2 , x , !y2
38. y − csc x 2 2sin x, 0 , x , !
39. y −
sin x
1 1 cos x
40. y −
41. y − arctanse x d
sin x
2 1 cos x
42. y − s1 2 xde x
43. y − 1ys1 1 e 2x d
44. y − e2x sin x,
45. y −
1
1 ln x
x
0 < x < 2!
46. y − x sln xd 2
47. y − s1 1 e x d22
48. y − e xyx 2
49. y − lnssin xd
50. y − lns1 1 x 3d
51. y − xe21yx
52. y −
53. y − e arctan x
54. y − tan21
ln x
x2
S D
x21
x11
55–58 The graph of a function f is shown. (The dashed lines
indicate horizontal asymptotes.) Find each of the following for the
given function t.
(a) The domains of t and t9
(b) The critical numbers of t
(c) The approximate value of t9s6d
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328
CHAPTER 4
Applications of Differentiation
(d) All vertical and horizontal asymptotes of t
section of the beam.) Sketch the graph of the deflection
curve.
y
y
W
f
0
L
1
0
x
1
55. tsxd − s f sxd
|
57. tsxd − f sxd
3
56. tsxd − s
f sxd
|
58. tsxd − 1yf sxd
59. In the theory of relativity, the mass of a particle is
m−
64. Coulomb’s Law states that the force of attraction between two
charged particles is directly proportional to the product of the
charges and inversely proportional to the square of the distance between them. The figure shows particles with charge 1
located at positions 0 and 2 on a coordinate line and a particle
with charge 21 at a position x between them. It follows from
Coulomb’s Law that the net force acting on the middle particle is
m0
Fsxd − 2
s1 2 v 2yc 2
where m 0 is the rest mass of the particle, m is the mass when
the particle moves with speed v relative to the observer, and c
is the speed of light. Sketch the graph of m as a function of v.
E − sm c 1 h c y(
4
2
2
2
where m 0 is the rest mass of the particle, ( is its wave length,
and h is Planck’s constant. Sketch the graph of E as a function of (. What does the graph say about the energy?
61. A model for the spread of a rumor is given by the equation
pstd −
1
1 1 ae2kt
where pstd is the proportion of the population that knows the
rumor at time t and a and k are positive constants.
(a) When will half the population have heard the rumor?
(b) When is the rate of spread of the rumor greatest?
(c) Sketch the graph of p.
62. A model for the concentration at time t of a drug injected into
the bloodstream is
Cstd − Kse
2at
2e
2bt
d
where a, b, and K are positive constants and b . a. Sketch
the graph of the concentration function. What does the graph
tell us about how the concentration varies as time passes?
63. The figure shows a beam of length L embedded in concrete
walls. If a constant load W is distributed evenly along its
length, the beam takes the shape of the deflection curve
W 4
WL 3
WL 2 2
x 1
x 2
x
y−2
24EI
12EI
24EI
where E and I are positive constants. (E is Young’s modulus of elasticity and I is the moment of inertia of a cross-
0,x,2
where k is a positive constant. Sketch the graph of the net
force function. What does the graph say about the force?
60. In the theory of relativity, the energy of a particle is
2
0
k
k
1
x2
sx 2 2d2
+1
_1
+1
0
x
2
x
65–68 Find an equation of the slant asymptote. Do not sketch the
curve.
65. y −
x2 1 1
x11
66. y −
4x 3 2 10x 2 2 11x 1 1
x 2 2 3x
67. y −
2x 3 2 5x 2 1 3x
x2 2 x 2 2
68. y −
26x 4 1 2x 3 1 3
2x 3 2 x
69–74 Use the guidelines of this section to sketch the curve. In
guideline D, find an equation of the slant asymptote.
69. y −
x2
x21
70. y −
1 1 5x 2 2x 2
x22
71. y −
x3 1 4
x2
72. y −
x3
sx 1 1d2
73. y − 1 1 12 x 1 e2x
74. y − 1 2 x 1 e 11xy3
75. Show that the curve y − x 2 tan21x has two slant asymptotes: y − x 1 !y2 and y − x 2 !y2. Use this fact to help
sketch the curve.
76. Show that the curve y − sx 2 1 4x has two slant asymptotes:
y − x 1 2 and y − 2x 2 2. Use this fact to help sketch the
curve.
77. Show that the lines y − sbyadx and y − 2sbyadx are slant
asymptotes of the hyperbola sx 2ya 2 d 2 s y 2yb 2 d − 1.
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SECTION 4.6
Graphing with Calculus and Technology
329
lim f f sxd 2 x 2 g − 0
79. Discuss the asymptotic behavior of f sxd − sx 4 1 1dyx in
the same manner as in Exercise 78. Then use your results to
help sketch the graph of f .
This shows that the graph of f approaches the graph of y − x 2,
and we say that the curve y − f sxd is asymptotic to the parabola y − x 2. Use this fact to help sketch the graph of f .
80. Use the asymptotic behavior of f sxd − sin x 1 e2x to sketch
its graph without going through the curve-sketching procedure of this section.
78. Let f sxd − sx 3 1 1dyx. Show that
x l 6`
4.6 Graphing with Calculus and Technology
You may want to read Graphing
Calculators and Computers at
www.StewartCalculus.com if you
haven’t already. In particular, it
explains how to avoid some of the pitfalls of graphing devices by choosing
appropriate viewing rectangles.
The method we used to sketch curves in the preceding section was a culmination of much
of our study of differential calculus. The graph was the final object that we produced. In
this section our point of view is completely different. Here we start with a graph produced by a graphing calculator or computer and then we refine it. We use calculus to
make sure that we reveal all the important aspects of the curve. And with the use of
graphing devices we can tackle curves that would be far too complicated to consider
without technology. The theme is the interaction between calculus and technology.
EXAMPLE 1 Graph the polynomial f sxd − 2x 6 1 3x 5 1 3x 3 2 2x 2. Use the graphs
of f 9 and f 0 to estimate all maximum and minimum points and intervals of concavity.
41,000
y=ƒ
_5
_1000
5
FIGURE 1
100
y=ƒ
f 9sxd − 12x 5 1 15x 4 1 9x 2 2 4x
_3
f 0sxd − 60x 4 1 60x 3 1 18x 2 4
2
_50
FIGURE 2
SOLUTION If we specify a domain but not a range, graphing software will often deduce a
suitable range from the values computed. Figure 1 shows a plot that may result if we specify
that 25 < x < 5. Although this viewing rectangle is useful for showing that the asymptotic
behavior (or end behavior) is the same as for y − 2x 6, it is obviously hiding some finer
detail. So we change to the viewing rectangle f23, 2g by f250, 100g in Figure 2.
Most graphing calculators and graphing software allow us to “trace” along a curve and
see approximate coordinates of points. (Some also have features to identify the approximate
locations of local maximum and minimum points.) Here it appears that there is an absolute
minimum value of about 215.33 when x < 21.62 and f is decreasing on s2`, 21.62d
and increasing on s21.62, `d. Also, there appears to be a horizontal tangent at the origin
and inflection points when x − 0 and when x is somewhere between 22 and 21.
Now let’s try to confirm these impressions using calculus. We differentiate and get
When we graph f 9 in Figure 3 we see that f 9sxd changes from negative to positive when
x < 21.62; this confirms (by the First Derivative Test) the minimum value that we
found earlier. But, perhaps to our surprise, we also notice that f 9sxd changes from
positive to negative when x − 0 and from negative to positive when x < 0.35. This
means that f has a local maximum at 0 and a local minimum when x < 0.35, but these
were hidden in Figure 2. Indeed, if we now zoom in toward the origin in Figure 4, we
1
20
y=ƒ
y=fª(x)
_1
_3
2
_1
_5
FIGURE 3
1
FIGURE 4
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330
CHAPTER 4
Applications of Differentiation
see what we missed before: a local maximum value of 0 when x − 0 and a local
minimum value of about 20.1 when x < 0.35.
What about concavity and inflection points? From Figures 2 and 4 there appear to
be inflection points when x is a little to the left of 21 and when x is a little to the
right of 0. But it’s difficult to determine inflection points from the graph of f , so we
graph the second derivative f 0 in Figure 5. We see that f 0 changes from positive
to negative when x < 21.23 and from negative to positive when x < 0.19. So, correct to two decimal places, f is concave upward on s2`, 21.23d and s0.19, `d and
concave downward on s21.23, 0.19d. The inflection points are s21.23, 210.18d
and s0.19, 20.05d.
We have discovered that no single graph reveals all the important features of this
polynomial. But Figures 2 and 4, when taken together, do provide an accurate picture.
10
_3
2
y=f ·(x)
_30
FIGURE 5
n
EXAMPLE 2 Draw the graph of the function
f sxd −
x 2 1 7x 1 3
x2
in a viewing rectangle that shows all the important features of the function. Estimate the
local maximum and minimum values and the intervals of concavity. Then use calculus to
find these quantities exactly.
SOLUTION Figure 6 — produced by graphing software with automatic scaling—is
a disaster. Some graphing calculators use f210, 10g by f210, 10g as the default
viewing rectangle, so let’s try it. We get the graph shown in Figure 7; it’s a major
improvement.
3 " 10!*
10
y=ƒ
_10
y=ƒ
_5
10
5
FIGURE 6
_10
FIGURE 7
The y-axis appears to be a vertical asymptote and indeed it is because
x 2 1 7x 1 3
−`
xl0
x2
lim
10
y=ƒ
y=1
20
_20
_5
FIGURE 8
Figure 7 also allows us to estimate the x-intercepts: about 20.5 and 26.5. The
exact values are obtained by using the quadratic formula to solve the equation
x 2 1 7x 1 3 − 0; we get x − (27 6 s37 )y2.
To get a better look at horizontal asymptotes, we change to the viewing rectangle
f220, 20g by f25, 10g in Figure 8. It appears that y − 1 is the horizontal asymptote
and this is easily confirmed:
S
x 2 1 7x 1 3
7
3
− lim 1 1 1 2
2
x l 6`
x
l
6`
x
x
x
lim
D
−1
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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.6
2
_3
0
331
Graphing with Calculus and Technology
To estimate the minimum value we zoom in to the viewing rectangle f23, 0g by
f24, 2g in Figure 9. We find that the absolute minimum value is about 23.1 when
x < 20.9, and we see that the function decreases on s2`, 20.9d and s0, `d and
increases on s20.9, 0d. The exact values are obtained by differentiating:
7
6
7x 1 6
f 9sxd − 2 2 2 3 − 2
x
x
x3
y=ƒ
_4
This shows that f 9sxd . 0 when 267 , x , 0 and f 9sxd , 0 when x , 267 and when
37
x . 0. The exact minimum value is f (2 67 ) − 2 12
< 23.08.
Figure 9 also shows that an inflection point occurs somewhere between x − 21 and
x − 22. We could estimate it much more accurately using the graph of the second
derivative, but in this case it’s just as easy to find exact values. Since
FIGURE 9
f 0sxd −
14
18
2s7x 1 9d
1 4 −
3
x
x
x4
we see that f 0sxd . 0 when x . 297 sx ± 0d and f 0sxd , 0 when x , 297. So f is
concave upward on (297 , 0) and s0, `d and concave downward on (2`, 297 ). The
inflection point is (297 , 271
27 ).
The analysis using the first two derivatives shows that Figure 8 displays all the
major aspects of the curve.
EXAMPLE 3 Graph the function f sxd −
10
_10
y=ƒ
10
_10
x 2sx 1 1d3
.
sx 2 2d2sx 2 4d4
SOLUTION Drawing on our experience with a rational function in Example 2, let’s
start by graphing f in the viewing rectangle f210, 10g by f210, 10g. From Figure 10
we have the feeling that we are going to have to zoom in to see some finer detail and
also zoom out to see the larger picture. But, as a guide to intelligent zooming, let’s
first take a close look at the expression for f sxd. Because of the factors sx 2 2d2 and
sx 2 4d4 in the denominator, we expect x − 2 and x − 4 to be the vertical asymptotes.
Indeed
x 2sx 1 1d3
−`
x l 2 sx 2 2d2sx 2 4d4
lim
FIGURE 10
n
and
x 2sx 1 1d3
−`
x l 4 sx 2 2d2sx 2 4d4
lim
To find the horizontal asymptotes, we divide numerator and denominator by x 6:
x 2 sx 1 1d3
!
x 2sx 1 1d3
x3
x3
−
−
2
4
2
sx 2 2d sx 2 4d
sx 2 2d
sx 2 4d4
!
x2
x4
y
_1
FIGURE 11
1
2
3
4
x
S D
S DS D
1
1
11
x
x
12
2
x
2
12
3
4
x
4
This shows that f sxd l 0 as x l 6`, so the x-axis is a horizontal asymptote.
It is also very useful to consider the behavior of the graph near the x-intercepts using
an analysis like that in Example 2.6.12. Since x 2 is positive, f sxd does not change sign
at 0 and so its graph doesn’t cross the x-axis at 0. But, because of the factor sx 1 1d3,
the graph does cross the x-axis at 21 and has a horizontal tangent there. Putting all this
information together, but without using derivatives, we see that the curve has to look
something like the one in Figure 11.
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332
CHAPTER 4
Applications of Differentiation
Now that we know what to look for, we zoom in (several times) to produce the
graphs in Figures 12 and 13 and zoom out (several times) to get Figure 14.
0.05
0.0001
500
y=ƒ
y=ƒ
_100
1
_1.5
0.5
y=ƒ
_0.05
_0.0001
FIGURE 12
FIGURE 13
_1
_10
10
FIGURE 14
We can read from these graphs that the absolute minimum is about 20.02 and
occurs when x < 220. There is also a local maximum <0.00002 when x < 20.3 and
a local minimum <211 when x < 2.5. These graphs also show three inflection points
near 235, 25, and 21 and two between 21 and 0. To estimate the inflection points
closely we would need to graph f 0, but to compute f 0 by hand is an unreasonable
chore. If you have a computer algebra system, then it’s easy to do (see Exercise 15).
We have seen that, for this particular function, three graphs (Figures 12, 13, and 14)
are necessary to convey all the useful information. The only way to display all these
features of the function on a single graph is to draw it by hand. Despite the exaggerations and distortions, Figure 11 does manage to summarize the essential nature of the
function.
n
EXAMPLE 4 Graph the function f sxd − sinsx 1 sin 2xd. For 0 < x < !, estimate
all maximum and minimum values, intervals of increase and decrease, and inflection
points.
1.1
|
y=ƒ
0
SOLUTION We first note that f is periodic with period 2!. Also, f is odd and
f sxd < 1 for all x. So the choice of a viewing rectangle is not a problem for this
function: we start with f0, !g by f21.1, 1.1g. (See Figure 15.) It appears that there are
three local maximum values and two local minimum values in that window. To confirm
these values and locate them more accurately, we calculate that
π
|
f 9sxd − cossx 1 sin 2xd ! s1 1 2 cos 2xd
_1.1
and graph both f and f 9 in Figure 16.
After estimating the values of the x-intercepts of f 9, we use the First Derivative Test
to find the following approximate values:
FIGURE 15
1.2
y=ƒ
0
π
y=fª(x)
Intervals of increase:
s0, 0.6d, s1.0, 1.6d, s2.1, 2.5d
Intervals of decrease:
s0.6, 1.0d, s1.6, 2.1d, s2.5, !d
Local maximum values: f s0.6d < 1, f s1.6d < 1, f s2.5d < 1
Local minimum values:
f s1.0d < 0.94, f s2.1d < 0.94
The second derivative is
_1.2
FIGURE 16
f 0sxd − 2s1 1 2 cos 2xd2 sinsx 1 sin 2xd 2 4 sin 2x cossx 1 sin 2xd
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SECTION 4.6
1.2
Graphing with Calculus and Technology
333
Graphing both f and f 0 in Figure 17, we obtain the following approximate values:
0
s0.8, 1.3d, s1.8, 2.3d
Concave upward on:
f
Concave downward on: s0, 0.8d, s1.3, 1.8d, s2.3, !d
π
_1.2
FIGURE 17
s0, 0d, s0.8, 0.97d, s1.3, 0.97d, s1.8, 0.97d, s2.3, 0.97d
Inflection points:
f·
Having checked that Figure 15 does indeed represent f accurately for 0 < x < !,
we can state that the extended graph in Figure 18 represents f accurately for
22! < x < 2!.
1.2
f
The family of functions
_2π
f sxd − sinsx 1 sin cxd
where c is a constant, occurs in applications to frequency modulation (FM)
synthesis. A sine wave is modulated
by a wave with a different frequency
ssin cxd. The case where c − 2 is studied in Example 4. Exercise 27 explores
another special case.
2π
_1.2
FIGURE 18
n
Our final example is concerned with families of functions. This means that the functions in the family are related to each other by a formula that contains one or more arbitrary constants. Each value of the constant gives rise to a member of the family and the
idea is to see how the graph of the function changes as the constant changes.
EXAMPLE 5 How does the graph of f sxd − 1ysx 2 1 2x 1 cd vary as c varies?
SOLUTION The graphs in Figures 19 and 20 (the special cases c − 2 and c − 22)
show two very different-looking curves.
2
_5
2
4
1
y=
≈+2x+2
_5
y=
1
≈+2x-2
4
_2
_2
FIGURE 19
FIGURE 20
c−2
c − 22
Before drawing any more graphs, let’s see what members of this family have in
common. Since
1
lim 2
−0
x l 6` x 1 2x 1 c
for any value of c, they all have the x-axis as a horizontal asymptote. A vertical asymptote will occur when x 2 1 2x 1 c − 0. Solving this quadratic equation, we get
x − 21 6 s1 2 c . When c . 1, there is no vertical asymptote (as in Figure 19).
When c − 1, the graph has a single vertical asymptote x − 21 because
lim
1
x l21 x 2 1 2x 1 1
− lim
1
x l21 sx 1 1d2
−`
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334
CHAPTER 4
Applications of Differentiation
When c , 1, there are two vertical asymptotes: x − 21 6 s1 2 c (as in Figure 20).
Now we compute the derivative:
2x 1 2
f 9sxd − 2 2
sx 1 2x 1 cd2
This shows that f 9sxd − 0 when x − 21 (if c ± 1), f 9sxd . 0 when x , 21, and
f 9sxd , 0 when x . 21. For c > 1, this means that f increases on s2`, 21d
and decreases on s21, `d. For c . 1, there is an absolute maximum value
f s21d − 1ysc 2 1d. For c , 1, f s21d − 1ysc 2 1d is a local maximum value and the
intervals of increase and decrease are interrupted at the vertical asymptotes.
Figure 21 is a “slide show” displaying five members of the family, all graphed in the
viewing rectangle f25, 4g by f22, 2g. As predicted, a transition takes place from two
vertical asymptotes to one for c − 1, and then to none for c . 1. As c increases from 1,
we see that the maximum point becomes lower; this is explained by the fact that
1ysc 2 1d l 0 as c l `. As c decreases from 1, the vertical asymptotes become more
widely separated because the distance between them is 2 s 1 2 c , which becomes large
as c l 2`. Again, the maximum point approaches the x-axis because 1ysc 2 1d l 0
as c l 2`.
c=_1
c=0
FIGURE 21
c=1
c=2
c=3
There is clearly no inflection point when c < 1. For c . 1 we calculate that
The family of functions
f sxd − 1ysx 2 1 2x 1 cd
f 0sxd −
2s3x 2 1 6x 1 4 2 cd
sx 2 1 2x 1 cd3
and deduce that inflection points occur when x − 21 6 s3sc 2 1dy3. So the inflection
points become more spread out as c increases and this seems plausible from the last
two graphs of Figure 21.
n
4.6
;
Exercises
1–8 Produce graphs of f that reveal all the important aspects of
the curve. In particular, you should use graphs of f 9 and f 0 to
estimate the intervals of increase and decrease, extreme values,
intervals of concavity, and inflection points.
7. f sxd − 6 sin x 1 cot x,
1. f sxd − x 5 2 5x 4 2 x 3 1 28x 2 2 2x
9–10 Produce graphs of f that reveal all the important aspects
of the curve. Estimate the intervals of increase and decrease
and intervals of concavity, and use calculus to find these intervals exactly.
2. f sxd − 22x 6 1 5x 5 1 140x 3 2 110x 2
3. f sxd − x 6 2 5x 5 1 25x 3 2 6x 2 2 48x
x4 2 x 3 2 8
x2 2 x 2 6
x
5. f sxd − 3
x 1 x2 1 1
9. f sxd − 1 1
4. f sxd −
6. f sxd − 6 sin x 2 x 2,
8. f sxd − e 2 0.186x
x
10. f sxd −
2! < x < !
4
1
8
1
1 2 1 3
x
x
x
1
2 3 10 8
8 2
x
x4
25 < x < 3
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SECTION 4.6
Graphing with Calculus and Technology
335
11–12
(a) Graph the function.
(b) Use l’Hospital’s Rule to explain the behavior as x l 0.
(c) Estimate the minimum value and intervals of concavity.
Then use calculus to find the exact values.
(c) Estimate the maximum and minimum values and then use
calculus to find the exact values.
(d) Use a computer algebra system to compute f 0. Then use a
graph of f 0 to estimate the x-coordinates of the inflection
points.
11. f sxd − x 2 ln x
25. f sxd − x 1yx
12. f sxd − xe 1yx
13–14 Sketch the graph by hand using asymptotes and
inter-cepts, but not derivatives. Then use your sketch as a guide
to producing graphs using a calculator or computer that display
the major features of the curve. Use these graphs to estimate the
maximum and minimum values.
13. f sxd −
sx 1 4dsx 2 3d2
x 4sx 2 1d
14. f sxd −
s2 x 1 3d 2 sx 2 2d 5
x 3 sx 2 5d 2
15. For the function f of Example 3, use a computer algebra
system to calculate f 9 and then graph it to confirm that all
the maximum and minimum values are as given in the
example. Calculate f 0 and use it to estimate the intervals of
concavity and inflection points.
16. For the function f of Exercise 14, use a computer algebra
system to find f 9 and f 0 and use their graphs to estimate the
intervals of increase and decrease and concavity of f .
17–22 Use a computer algebra system to graph f and to find f 9
and f 0. Use graphs of these derivatives to estimate the intervals
of increase and decrease, extreme values, intervals of concavity,
and inflection points of f .
17. f sxd −
18. f sxd −
x 3 1 5x 2 1 1
4
x 1 x3 2 x2 1 2
19. f sxd − sx 1 5 sin x ,
28–35 Describe how the graph of f varies as c varies. Graph
several members of the family to illustrate the trends that you
discover. In particular, you should investigate how maximum
and minimum points and inflection points move when c changes.
You should also identify any transitional values of c at which the
basic shape of the curve changes.
28. f sxd − x 3 1 cx
29. f sxd − x 2 1 6 x 1 cyx (trident of Newton)
30. f sxd − x sc 2 2 x 2
31. f sxd − e x 1 ce2x
32. f sxd − lnsx 2 1 cd
33. f sxd −
34. f sxd −
x < 20
20. f sxd − x 2 tan21sx 2 d
21. f sxd −
1 2 e 1yx
1 1 e 1yx
22. f sxd −
3
3 1 2 sin x
1 2 cossx 4 d
x8
sin x
c 1 cos x
cx
1 1 c 2x 2
35. f sxd − cx 1 sin x
36. The family of functions f std − Cse2at 2 e2bt d, where a,
b, and C are positive numbers and b . a, has been used to
model the concentration of a drug injected into the bloodstream at time t − 0. Graph several members of this family.
What do they have in common? For fixed values of C and a,
discover graphically what happens as b increases. Then use
calculus to prove what you have discovered.
23–24 Graph the function using as many viewing rectangles as
you need to depict the true nature of the function.
23. f sxd −
27. In Example 4 we considered a member of the family of
functions f sxd − sinsx 1 sin cxd that occur in FM synthesis. Here we investigate the function with c − 3. Start by
graphing f in the viewing rectangle f0, !g by f21.2, 1.2g.
How many local maximum points do you see? The graph
has more than are visible to the naked eye. To discover the
hidden maximum and minimum points you will need to
examine the graph of f 9 very carefully. In fact, it helps to
look at the graph of f 0 at the same time. Find all the maximum and minimum values and inflection points. Then
graph f in the viewing rectangle f22!, 2!g by f21.2, 1.2g
and comment on symmetry.
2y3
x
1 1 x 1 x4
26. f sxd − ssin xdsin x
|
24. f sxd − e x 1 ln x 2 4
25–26
(a) Graph the function.
(b) Explain the shape of the graph by computing the limit as
x l 01 or as x l `.
|
37. Investigate the family of curves given by f sxd − xe2cx,
where c is a real number. Start by computing the limits as
x l 6`. Identify any transitional values of c where the
basic shape changes. What happens to the maximum or
minimum points and inflection points as c changes? Illustrate by graphing several members of the family.
38. The figure shows graphs (in blue) of several members of the
family of polynomials f sxd − cx 4 2 4x 2 1 1.
(a) For which values of c does the curve have minimum
points?
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336
CHAPTER 4
Applications of Differentiation
(b) Show that the minimum and maximum points of every
curve in the family lie on the parabola y − 22x 2 1 1
(shown in red).
y
39. Investigate the family of curves given by the equation
f sxd − x 4 1 cx 2 1 x. Start by determining the transitional
value of c at which the number of inflection points changes.
Then graph several members of the family to see what
shapes are possible. There is another transitional value
of c at which the number of critical numbers changes.
Try to discover it graphically. Then prove what you have
discovered.
40. (a) Investigate the family of polynomials given by the
equation
f sxd − 2x 3 1 cx 2 1 2 x
2
1
x
For what values of c does the curve have maximum and
minimum points?
(b) Show that the minimum and maximum points of
every curve in the family lie on the curve y − x 2 x 3.
Illustrate by graphing this curve and several members
of the family.
4.7 Optimization Problems
PS
The methods we have learned in this chapter for finding extreme values have practical
applications in many areas of life: A businessperson wants to minimize costs and maximize
profits. A traveler wants to minimize transportation time. Fermat’s Principle in optics states
that light follows the path that takes the least time. In this section we solve such problems
as maximizing areas, volumes, and profits and minimizing distances, times, and costs.
In solving such practical problems the greatest challenge is often to convert the word
problem into a mathematical optimization problem by setting up the function that is to
be maximized or minimized. Let’s recall the problem-solving principles discussed in the
Principles of Problem Solving following Chapter 1 and adapt them to this situation:
Steps In Solving Optimization Problems
1. Understand the Problem The first step is to read the problem carefully until
it is clearly understood. Ask yourself: What is the unknown? What are the given
quantities? What are the given conditions?
2. Draw a Diagram In most problems it is useful to draw a diagram and identify
the given and required quantities on the diagram.
3. Introduce Notation Assign a symbol to the quantity that is to be maximized or
minimized (let’s call it Q for now). Also select symbols sa, b, c, . . . , x, yd for other
unknown quantities and label the diagram with these symbols. It may help to use
initials as suggestive symbols—for example, A for area, h for height, t for time.
4. Express Q in terms of some of the other symbols from Step 3.
5. If Q has been expressed as a function of more than one variable in Step 4, use
the given information to find relationships (in the form of equations) among
these variables. Then use these equations to eliminate all but one of the variables in the expression for Q. Thus Q will be expressed as a function of one
variable x, say, Q − f sxd. Write the domain of this function in the given context.
6. Use the methods of Sections 4.1 and 4.3 to find the absolute maximum or
minimum value of f. In particular, if the domain of f is a closed interval, then
the Closed Interval Method in Section 4.1 can be used.
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SECTION 4.7
Optimization Problems
337
EXAMPLE 1 A farmer has 2400 ft of fencing and wants to fence off a rectangular field
that borders a straight river. He needs no fence along the river. What are the dimensions
of the field that has the largest area?
SOLUTION In order to get a feeling for what is happening in this problem, let’s experiment with some specific cases. Figure 1 (not to scale) shows three possible ways of
laying out the 2400 ft of fencing.
PS Understand the problem
PS Analogy: Try special cases
PS Draw diagrams
400
1000
2200
100
100
Area=100 · 2200=220,000 ft@
FIGURE 1
y
A
1000
700
Area=700 · 1000=700,000 ft@
1000
Area=1000 · 400=400,000 ft@
We see that when we try shallow, wide fields or deep, narrow fields, we get relatively small areas. It seems plausible that there is some intermediate configuration that
produces the largest area.
Figure 2 illustrates the general case. We wish to maximize the area A of the rectangle. Let x and y be the depth and width of the rectangle (in feet). Then we express A
in terms of x and y:
A − xy
PS Introduce notation
x
700
x
We want to express A as a function of just one variable, so we eliminate y by expressing it in terms of x. To do this we use the given information that the total length of the
fencing is 2400 ft. Thus
2x 1 y − 2400
FIGURE 2
From this equation we have y − 2400 2 2x, which gives
A − xy − xs2400 2 2xd − 2400x 2 2x 2
Note that the largest x can be is 1200 (this uses all the fence for the depth and none for
the width) and x can’t be negative, so the function that we wish to maximize is
Asxd − 2400x 2 2x 2
0 < x < 1200
The derivative is A9sxd − 2400 2 4x, so to find the critical numbers we solve the
equation
2400 2 4x − 0
which gives x − 600. The maximum value of A must occur either at this critical
number or at an endpoint of the interval. Since As0d − 0, As600d − 720,000,
and As1200d − 0, the Closed Interval Method gives the maximum value as
As600d − 720,000.
[Alternatively, we could have observed that A0sxd − 24 , 0 for all x, so A is
always concave downward and the local maximum at x − 600 must be an absolute
maximum.]
The corresponding y-value is y − 2400 2 2s600d − 1200, so the rectangular field
should be 600 ft deep and 1200 ft wide.
n
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338
CHAPTER 4
Applications of Differentiation
EXAMPLE 2 A cylindrical can is to be made to hold 1 L of oil. Find the dimensions
that will minimize the cost of the metal to manufacture the can.
SOLUTION Draw a diagram as in Figure 3, where r is the radius and h the height (both
in centimeters). In order to minimize the cost of the metal, we minimize the total surface
area of the cylinder (top, bottom, and sides). From Figure 4 we see that the sides are
made from a rectangular sheet with dimensions 2!r and h. So the surface area is
h
r
A − 2!r 2 1 2!rh
FIGURE 3
We would like to express A in terms of one variable, r. To eliminate h we use the
fact that the volume is given as 1 L, which is equivalent to 1000 cm3. Thus
2πr
r
!r 2h − 1000
h
which gives h − 1000ys!r 2 d. Substitution of this into the expression for A gives
A − 2!r 2 1 2!r
Area 2{πr@}
Area (2πr)h
FIGURE 4
S D
1000
!r 2
− 2!r 2 1
2000
r
We know that r must be positive, and there are no limitations on how large r can be.
Therefore the function that we want to minimize is
Asrd − 2!r 2 1
2000
r
r.0
To find the critical numbers, we differentiate:
A9srd − 4!r 2
y
y=A(r)
1000
0
10
r
FIGURE 5
In the Applied Project following this
section we investigate the most economical shape for a can by taking into
account other manufacturing costs.
2000
4s!r 3 2 500d
−
r2
r2
3
Then