Instructor:
Telephone:
Office:
Hours:
IUPUI— SPRING 2014
Syllabus for E270—Section 10347 (Web-Based)
Shahrokh Towfighi
e-mail: stowfig@iupui.edu
278-7213 (Office). Leave a clear message.
CA 513
MW—1:00-3:00
If you cannot meet me at these hours, please make an appointment.
TEACHING/LEARNING MATERIAL
Lecture Notes
My notes are available on the web: www.iupui.edu/~towfighi in folder /e270.
Lecture Videos
Lecture Videos are available at the following website:
http://www.imds.iupui.edu/imds/bb.shtml#EE
Once there, scroll down the series of videos for E270. They are labeled according to the Lecture
Notes chapter heading.
Anderson, Sweeney, Williams, Statistics for Business and Economics (Eleventh Edition, Jan 1, 2010)
This text book is intended for students who feel the need for an additional resource. Do not buy this
book immediately. Wait to see if you need it, which most likely will NOT. You may find a used one on
the Web for a low price.
COURSE REQUIREMENTS
Homework 1-7
Homework “Final”
Tests
Common Final
30%
10%
25%
35%
100%
Homework Assignments
There is a homework problem file for each of the seven chapters in the syllabus. Check the schedule below for the due dates.
You must submit the homework assignments no later than the due date. Check the grade roster frequently for your scores. At
times, for one reason or other, some homework assignments do not find their way to my e-mail address. If you send a
homework and you do not see the score for that homework on the grade roster, let me know immediately. Otherwise, I will
assume you never sent the assignment and you will get a 0 for that.
How to Turn in Your Homework Assignments (PLEASE READ CAREFULLY)
The homework assignments are Excel files and will be posted on (and emailed via) Oncourse. All homework problems are
multiple choice. Enter your answers in the shaded column shown in the Excel worksheet as shown below:
Enter your LETTER answers HERE
↓
1 a
2 c
3 d
4 b
5 b
You must enter only the letter. No other characters are admissible, including space. Also in the same worksheet you see the
instructions for saving and e-mailing the file. Please follow the instructions carefully.
Send your e-mails to stowfig@iupui.edu. Do not send your files to Oncourse.
Practice Problems
Multiple choice practice problems in Excel files are provided for each chapter, easily located on my
website. These problems are very useful in preparing you to answer homework and test questions.
E-MAIL COMMUNICATION
Homework and test files, plus all other announcements will be posted on (and emailed via) Oncourse to you. However, you
must send your homework and test files as attachments to my own e-mail address stowfig@iupui.edu. Also any questions
and issues you need to discuss with me, do it via my e-mail.
Homework Assignments
There is a homework problem file for each of the first seven chapters in the syllabus. Each problem set is due following the
completion of each chapter. These homework files will be e-mailed to you. The due dates are shown below. Check the grade
roster frequently for your scores. At times, for one reason or other, some homework assignments do not find their way to my
e-mail address. If you send a homework and you do not see the score for that homework on the grade roster, let me know
immediately. Otherwise, I will assume you never sent the assignment and you will get a 0 for that.
Solutions to homework assignments will be posted on (and emailed via) Oncourse after the deadline. This clearly
means that I will not accept a homework assignment after the deadline.
HOW TO TURN IN YOUR TEST ANSWERS
There will be seven tests, one for each of the 7 Lecture Notes chapters, plus a final which will cover chapters 4-7. Each test will
be posted on and emailed via Oncourse 24 hours after each homework deadline. Then you will have 24 hours to turn in your
tests. Each test has 10 multiple choice questions.
Letter grades are assigned based on the following schedule (scores are percentages computed from all the test and homework
assignment scores):
97
93
90
86
83
80
to
to
to
to
to
to
100
96
92
89
85
82
A+
A
AB+
B
B-
76
73
70
60
Under
to
to
to
to
79
75
72
69
60
C+
C
CD
F
IMPORTANT ISSUES CONCERNING COURSE GRADES
 You must take all the tests.
 Scores on tests are not curved.
 No extra assignments or credits to improve grade.
Your course grades are objectively determined according to your numeric scores and the letter grade schedule above.
I use Excel commands to automatically assign the letter grades to your bottom line score. So, if your bottom line score
is 89, then the grade is B+. At times, some students ask for an extra point to move their grade up one notch to, say,
from B+ to A-. The answer to this request is always NO. Please do not make such a request.
TOPICS
Chapter 1—Introduction to Statistics. Basic Concepts
Chapter 2—Random Variables and Probability Distributions
Chapter 3—The Normal Distribution
Chapter 4—Introduction to Statistical Inference: Sampling Distributions
Chapter 5—Interval Estimates for Population Parameters
Chapter 6—Hypothesis Testing
Chapter 7—Regression
ASSIGNMENTS AND DATES
The due dates you see below are the deadlines. Since all the homework files are provided to you in advance, you should
submit the assignments by the stated deadlines. You may submit the homework assignments any day you wish, as long as you
do not go past the specific deadline for each homework assignment. However, you will receive the solution to each homework
assignment only after the deadline for that homework.
Since you are provided this flexibility, NO HOMEWORK ASSIGNMENT WILL BE ACCEPTED PAST THE DEADLINE. If you have
any serious conflicts with TEST DEADLINES, please let me know.
The Departmental Common Final is mandatory. Please make plans from now to take the final ON CAMPUS
on the announced date: Thursday, December 12, 8:00-10:00 am in Lecture Hall, Room (TBA). You cannot
miss it!
ASSIGNMENT DEADLINES
The Departmental Common Final is mandatory. Please make plans from now to take the final on the
announced date: Thursday, May 08, 8:00-10:00 am in Lecture Hall, Room TBA. You shall not miss it!
No.
1.
2.
3.
4.
5.
6.
7.
8.
HOMEWORK
Due
Sat Jan 18
Sat Feb 01
Wed Feb 12
Tue Feb 25
Mon Mar 10
Sat Mar 29
Wed Apr 16
Sat May 03
5:00 PM
5:00 PM
5:00 PM
5:00 PM
5:00 PM
5:00 PM
5:00 PM
5:00 PM
No.
1.
2.
3.
4.
5.
6.
7.
Final
TESTS
Posted
Due
Sun Jan 19 5:00 PM
Mon Jan 20 8:00 PM
Sun Feb 02 5:00 PM
Mon Feb 03 8:00 PM
Thu Feb 13 5:00 PM
Fri Feb 14 8:00 PM
Wed Feb 26 5:00 PM
Thu Feb 27 8:00 PM
Tue Mar 11 5:00 PM
Wed Mar 12 8:00 PM
Sun Mar 30 5:00 PM
Mon Mar 31 8:00 PM
Thu Apr 17 5:00 PM
Fri Apr 18 8:00 PM
Thu May 08
8:00-10:00 AM (on campus)
OUTLINE OF THE TOPICS
Lecture Notes Chapter 1—Descriptive Statistics
ASW Chapter 1—Data and Statistics
Section 1.4—Descriptive Statistics (pp 13-15)
Section 1.5—Statistical Inference (pp 15, 16)
ASW CH3—Descriptive Statistics: Numerical Measures
Section 3.1—Measures of Location
Mean (pp 87, 88)
Section 3.2—Measures of Variability
Variance (pp 97-99)
Standard Deviation (p 99)
Section 3.3—z-Scores (pp 103, 104)
Section 3.6—The Weighted Mean (pp 124, 125)
ASW CH3 Exercises ASW Exercises are for practice only.
 For the following exercises compute the variance and standard deviation only: 15, 16, 18, 20, 24.
 Do all of 60 and 62 (These are exercises for the mean, variance, standard deviation, and z-score.)
 For weighted mean: 52, 54, 56
Lecture Notes Chapter 2—Random Variable and Probability Distribution
ASW Chapter 5—Discrete probability Distributions
Section 5.1—Random Variables
Section 5.2—Discrete Probability Distributions (Exercises: 7, 8, 10, 12, and 14)
Section 5.3—Expected Value and Variance (Exercises: 16, 18, 20, 22)
Section 5.4—Binomial Probability Distribution (Exercises: 26, 28, 32, 34, 36)
NOTES ABOUT SYMBOLS AND FORMULAS IN ASW:
Probability of success in binomial distribution— Lecture Notes:
ASW text:
Binomial distribution formula—
Lecture Notes:
ASW text:
π
p
𝑓(𝑥) = C(𝑛, 𝑥)𝜋 𝑥 (1 − 𝜋)(𝑛−𝑥)
𝑛
𝑓(𝑥) = ( ) 𝑝 𝑥 (1 − 𝑝)(𝑛−𝑥)
𝑥
Lecture Notes Chapter 3—Normal Distribution
ASW CH 6—Continuous Probability Distributions
Section 6.2—Normal Probability Distribution (Exercises: 10, 12, 13, 14, 15, 16, 18, 20, 22, 40, 42, 44, 46, 48)
NOTES ABOUT SYMBOLS AND FORMULAS:
Standard error of 𝑥̅ :
Lecture Notes:
ASW text:
Symbol for the population proportion:
Standard error of p̅ :
se(𝑥̅ ) =
σ𝑥 =
𝜎
σ
√𝑛
√𝑛
Lecture Notes:
ASW text:
π
p
Lecture Notes:
𝜋(1 − 𝜋)
se(𝑝̅ ) = √
𝑛
ASW text:
σ𝑝 = √
𝑝(1 − 𝑝)
𝑛
Lecture Notes CH5—Statistical Inference: Interval Estimates
ASW CH 8—Interval Estimation
Section 8.1—Population Mean: σ known (Exercises: 2, 4, 5, 8, 10)
Section 8.2—Population Mean: σ unknown (Exercises: 12, 13, 14, 15, 17, 20, 22)
Section 8.3—Determining the Sample Size (Exercises: 23, 24, 25, 26, 28, 30)
Section 8.4—Population Proportion (Exercises: 31, 32, 33, 34, 35, 36, 38, 39, 40, 42)
Supplementary Exercises: 44, 46, 50, 52, 54, 56, 58, 60
NOTES ABOUT SYMBOLS AND FORMULAS IN ASW:
Sample size formula (confidence interval for µ)—
Lecture Notes:
ASW text:
Sample size formula (confidence interval for π)—
𝑧α⁄2 σ
̂ 2
𝑛=(
)
MOE
2
(𝑧α⁄2 ) σ2
𝑛=
𝐸2
Lecture Notes:
𝑛=(
ASW text:
𝑛=
𝑧α⁄2 2
) π
̂(1 − π
̂)
MOE
2
(𝑧α⁄2 ) 𝑝∗ (1 − 𝑝∗ )
𝐸2
Lecture Notes Chapter 6—Statistical Inference: Hypothesis Tests
ASW Chapter 9—Hypothesis Tests
Section 9.1—Developing Null and Alternative Hypotheses (Exercises: 1, 2, 4)
Section 9.2—Type I and Type II Errors (Exercises: 5, 6, 8)
Section 9.3—Population Mean: σ Known (Exercises: 10, 11, 12, 14, 15, 16, 18, 20, 22)
Section 9.4—Population Mean: σ Unknown (Exercises: 24, 26, 27, 28, 30)
Section 9.5—Population Proportion (Exercises: 36, 38, 40)
Supplementary Exercises: 60, 62, 66, 68, 70
NOTES ABOUT SYMBOLS AND FORMULAS IN ASW:
The symbol for “alternative hypothesis”
Lecture Notes: H₁
ASW text:
Ha
Decision Rule (Rejection Rule) Critical Value Approach:
In the Lecture Notes the test statistic z or t are computed as absolute values (ignoring the algebraic sign “−“ or “+”). The ASW
text includes the algebraic sign. Please note the difference between the way the decision rule is stated in the Lecture Notes
and the ASW text. Of course, both lead to the same conclusion about the test. I prefer my way because it is simpler and less
confusing. This is because there is only one critical value approach decision rule for all the different types of tests.
▪ Decision Rule for a Lower Tail Test (Critical Value Approach)—
Lecture Notes:
Reject H₀ if TS > CV
𝑥̅ − µ
TS: |𝑧| =
CV = 𝑧α
𝑠𝑒(𝑥̅ )
𝑥̅ − µ
CV = 𝑡α,(df)
TS: |𝑡| =
𝑠𝑒(𝑥̅ )
ASW text:
Reject H₀ if z ≤ −zα
▪ Decision Rule for a Two-Tail Test (Critical Value Approach)—
Lecture Notes:
Reject H₀ if TS > CV
𝑥̅ − µ
TS: |𝑧| =
CV = zα/2
𝑠𝑒(𝑥̅ )
𝑥̅ − µ
TS: |𝑡| =
CV = tα/2,(df)
𝑠𝑒(𝑥̅ )
ASW text:
Reject H₀ if z ≤ −zα/2 or if z ≥ zα/2
Reject H₀ if t ≤ −tα/2,(df) or if t ≥ tα/2,(df)
Lecture Notes Chapter 7—Regression
ASW Chapter 14—Simple Linear Regression
Section 14.1—Simple Linear Regression Model
Section 14.2—Least Squares Method (Exercises: 1, 2, 4, 6)
NOTES ABOUT SYMBOLS AND FORMULAS IN ASW:
Least square formula for the slope coefficient:
Lecture Notes:
b₁ =
ASW text:
b₁ =
 xy  nxy
 x2  nx 2
 ( x  x )( y  y )
 ( x  x )2
Section 14.3—Coefficient of Determination (Exercises: 18-a, 18-b, 22, 22-a, 22-b)
Section 14.5—Testing for Significance [omit the subsection about F Test—pp 588-591] [Exercises: 24 (skip part d), 26
(skip parts b and c), 30]
NOTES ABOUT SYMBOLS AND FORMULAS IN ASW:
SSE
Mean Square Error:
Lecture Notes: var(e) =
n2
SSE
ASW text:
s² =
n2
Standard Error of Estimate
Standard Error of the Slope Coefficient
Lecture Notes:
se(e) =
ASW text:
s=
Lecture Notes:
se(b₁) =
ASW text:
sb1 =
SSE
n2
SSE
n2
se(e)
 ( x  x )2
s
 ( x  x )2
Note that ASW use the term “standard deviation” of b₁ rather than “standard error” of b₁.