MATH 210 - Introduction to Statistics - Spring 2008
MWF 1:00–1:50 in SCIC 122
Thursday Computer Labs in SCIC 142: Lab A = 12:30–1:45; Lab B = 2:00–3:15
Jim Brumbaugh-Smith
Campus Mail: Box 111
Phone: 982-5011
E-mail: jpbrumbaugh-smith@manchester.edu
Web: users.manchester.edu/facstaff/jpbrumbaugh-smith/index.htm
Office Hours in Science 120:
See instructor’s weekly schedule.
Description: This course introduces the fundamental principles of statistical analysis. This includes collection
of data, graphic representation of numerical data, the concepts of randomness and variability in sampling,
estimating a population’s numerical characteristics, testing conjectures about a population based on a
manageable-size sample, and developing linear prediction models using two-variable data.
Related Curriculum: It is strongly recommended that students have basic algebra skills comparable to MATH
112: College Algebra and computer skills comparable to CPTR 101: Introduction to Computers. This course is
required or recommended for majors in business, accounting, social sciences, natural sciences, and exercise
science, and satisfies the general education mathematics requirement.
Resources:
 REQUIRED: Introduction to the Practice of Statistics (IPS), 5th ed. by Moore and McCabe (ISBN
0-7167-6400-8).
 REQUIRED: Handbook for Introduction to Statistics, Spring 2008 by Brumbaugh-Smith (available at the
Campus Store)
 REQUIRED (but may be shared with a lab partner): SPSS Manual for Moore and McCabe’s IPS, 5th ed. by
Sorensen (ISBN 0-7167-6363-X)
 OPTIONAL: Study Guide for Moore and McCabe’s IPS, 5th ed. by Fligner (ISBN 0-7167-6358-3)
 Statistical Package for Social Sciences (SPSS) Version 15.0, available in the following campus labs: Science
142, Funderburg, Clark 102, all residence halls.
 You should have a basic calculator (with at least square roots and memory keys, for example a TI-30) and a
stapler (for submitting your homework). Graph paper may also come in handy.
Overview: This course relies heavily on the use of computer software to motivate and demonstrate statistical
concepts. On Thursdays we will usually meet in the computer lab, Science 142 These labs demonstrate various
statistical concepts and familiarize you with the statistical software for use in assignments. Homework will be
assigned each week and generally collected on Monday or Tuesday. There will also be three computer
assignments involving data analysis using the SPSS software.
Evaluation:
3 One-hour Tests (100 pts. each)
10 Homeworks (10 pts. each)
3 Computer Assignments (25 pts. each)
Cumulative Final Exam
Course Total
300
100
75
200
675
(44%)
(15%)
(11%)
(30%)
(100%)
95=A 90=A 87=B+ 83=B 80=B 77=C+ 73=C 70=C 67=D+ 63=D 60=D (**)
** In addition to having an overall average of 60%, to pass the course you must achieve at least an average of
55% on the tests and final exam.
Attendance: To maximize your learning and your grade it is important to participate in each class session. Note
that computer labs are an integral part of the course and are not to be considered optional. Please let me know in
advance if you are unable to attend class. Messages can be left twenty-four hours a day at 982-5011 or by e-mail.
Students are responsible for material covered and assignments made when absent. Tests will be made up by
advance arrangement only.
Approximate Schedule:
Jan
Feb
Mar
`
Apr
May
30
31
1
W
R
F
LAB #1
1.1
Introduction - “Data: What Good Is It?”
Introduction to SPSS / Course Web Page
Picturing Data - Stem Plots, Histograms
4
6
7
8
M
W
R
F
1.1
1.2
LAB #2
1.2
Measures of Center and Position
Descriptive Statistics
Measures of Variation, Boxplots
HW #1
11
13
14
15
M
W
R
F
1.3
1.3
LAB #3
3.1, 3.3
Density Curves, Normal Distributions
Normal Calculations
Assessing Normality/Linear Transformations
Sampling Methods
HW #2
18
20
21
22
M
W
R
F
3.3
Simple Random Samples
3.2
Studying Causation
TEST #1 Chapters 1 & 3
3.2
25
27
28
29
M
W
R
F
3.4
4.1, 4.2
4.2
4.2
Sampling Distributions
Intro to Probability
Probability Problem Solving
3
5
6
7
M
W
R
F
4.3
4.4
LAB #4
5.1
Random Variables (RVs)
Means and Variances of RVs
Uniform Distributions / Generating Random Numbers
Binomial Experiments
HW #4
10
12
13
14
M
W
R
F
5.1
5.2
TEST #2
5.2
Normal Approximation to Binomial Probabilities
Distribution of Sample Means
Chapters 4 & 5
Central Limit Theorem
HW #5
17−21
M−F
Spring Break
24
26
27
28
M
W
R
F
6.1
6.1
6.2
6.2
Estimating a Population Mean
HW #6
Significance Tests
Meet in classroom.
31
2
3
4
M
W
R
F
6.3, 6.4
7.1
7.1
7.2
Further Issues in Significance Testing
Inference Using the t-statistic
Matched Pairs
Comparing Two Population Means
HW #7
7
9
10
11
M
W
R
F
7.2
14
16
17
18
M
W
R
F
8.1
TEST #3 Chapters 6,7 & 8
8.2
Comparing Two Population Proportions
21
23
24
25
M
W
R
F
8.2
2.1
LAB #6
2.3
Relationships in Two-Variable Data
Relationships in Two-Variable Data
Linear Regression
Cptr Assignemnt #2 Due
28
30
1
2
M
W
R
F
2.3, 2.2
2.4
LAB #7
10.1
Linear Regression, Correlation
Issues for Correlation and Regression
Inference for Regression
Inference for Regression
HW #10
5
7
8
9
M
W
R
F
9.4
9.4
LAB #5
8.1
SCIC 142 (Lab A) 12:30–1:45; (B) 2:00–3:15
HW #3
12:30-1:45 & 2:00-3:15 in SCIC 122
Cptr Assignemnt #1 Due
Meet in classroom.
12:30-1:45 & 2:00-3:15 in SCIC 122
HW #8
T-Tests for Means
Inference for a Population Proportion
HW #9
12:30-1:45 & 2:00-3:15 in SCIC 122
Regression Overview
Multinomial Experiments
Cptr Assignemnt #3 Due
Exam Review
HW #11
Week of May 12 – Cumulative Final Exam