Math 386 Linear Statistical Models

Spring 2006

Section 001 8:00 to 9:00, M W F

Instructor: Dr. Chris Edwards   Phone: 424-1358 or 948-3969       Office: Swart 123

Classroom: Swart 302     Text: Applied Linear Statistical Models, 5th edition, by Kutner, Nachtsheim, Neter, and Li.

Grading: Final grades are based on these 500 points:

 

Topic

Points

Tentative Date

Chapters

Exam 1

One-Factor ANOVA

100 pts.

February 27

15-18

Exam 2

Multifactor ANOVA

100 pts.

April 10

19,20,21,23

Exam 3

Experimental Designs

100 pts.

May 8

24-29

Exam 4

Optional Final

100 pts.

May 12

15-29 (w/o 22)

Homework

 

200 pts.

Mostly Weekly

 

Final grades are assigned as follows:

450 pts. or more  A (90 %)
425 pts. or more  AB (85 %)
400 pts. or more  B (80 %)
375 pts. or more  BC (75 %)
350 pts. or more  C (70 %)
325 pts. or more  CD (65 %)
300 pts. or more  D (60 %)
299 pts. or less   F

Make-up exams will not be given. Exam 4, however, is an optional cumulative exam and will replace the lowest exam score. If any exam is missed for any reason, Exam 4 will replace that score.

Homework: There will be eight homework assignments each worth 25 points. Cooperation on homework is encouraged; copying is not. You are urged to work together on homework to solve problems; however, each of you must submit your own write-up.

Office Hours: Office hours are times when I will be in my office to help you. There are many other times when I am in my office. If I am in and not busy, I will be happy to help. My office hours for Fall 2005 semester are 3:00 to 4:00 Monday, Wednesday, and Friday, and 2:00 to 2:50 Tuesday, or by appointment.

Philosophy: I strongly believe that you, the student, are the only person who can make yourself learn. Therefore, whenever it is appropriate, I expect you to "discover" the mathematics we will be exploring. I do not feel that "lecturing" to you will teach you how to do mathematics. I hope to be your "guide" while we learn some mathematics, but you will need to do the learning. I expect each of you to come to class prepared to discuss the dayís material. That means you will have to pre-read each section of the text very carefully before class.

My idea of education is not "Teaching is telling and learning is listening". I believe that you must be active in the learning process to learn well. My job as a teacher, therefore, is not to "tell" you the answers to the problems we will encounter; rather it is to point you in a direction that will allow you to see the solutions yourselves. To accomplish that goal, I will work to find different interactive activities for us to work on. Your job is to use me, your text, your friends, and any other sources as resources. Remember, the goal is to learn mathematics, not to pass the exam. (Incidentally, if you have truly learned the material, the test results will take care of themselves.)

Homework Assignments:

Homework 1, due Feb 13

Chapter 15: 15.13, 15.22
Chapter 16: 16.7, 16.25

Homework 2, due Feb 24

Chapter 17: 17.8, 17.14, 18.4, 18.23

Homework 3, due Mar 10

Chapter 19: 19.6, 19.14, 19.15, 19.32

Homework 4, due Mar 29

Chapter 20: 20.2, 20.4
Chapter 21: 21.5, 21.6

Homework 5, due Apr 7

Chapter 23: 23.4
Chapter 24: 24.12, 24.13
Chapter 25: 25.3

Homework 6, due Apr 21

Chapter 26: 26.9, 26.10
Chapter 27: 27.3, 27. 4

Homework 7, due Apr 28

Chapter 28: 28.6, 28.7, 28.14, 28.15

Homework 8, due May 5

Chapter 29: 29.7, 29.20, 29.21, 29.22

 


Monday

Wednesday

Friday

Jan 30
Introduction / 301 review

Feb 1
Overview of Experimental Design

Feb 3
Single Factor ANOVA

Feb 6
SS Partitioning

Feb 8
Alternative Model

Feb 10
Power

Feb 13
Homework 1 due
Contrasts

Feb 15
Multiple Comparisons

Feb 17
Multiple Comparisons

Feb 20
Diagnostics

Feb 22
Remedial Measures

Feb 24
Homework 2 due
Review

Feb 27
Exam 1

Mar 1
Two Factor ANOVA, with Replicates

Mar 3
Two Factor ANOVA

Mar 6
Two Factor Multiple Comparisons

Mar 8
Two Factor, No Replicates

Mar 10
Homework 3 due
Randomized Blocks

Mar 20
Randomized Blocks

Mar 22
Two Factor, Unequal Sample Sizes: Model

Mar 24
Two Factor, Unequal Sample Sizes: Comparisons

Mar 27
Homework 4 due
Multi-Factor Models

Mar 29
Multi-Factor Tests

Mar 31
NO CLASS

Apr 3
Random Models

Apr 5
Mixed Models

Apr 7
Homework 5 due
Review

Apr 10
EMS Rules
Exam 2

Apr 12
Nested Designs

Apr 14
Repeated Measures

Apr 17
Split Plots

Apr 19
BIBDís

Apr 21
Homework 6 due
BIBDís

Apr 24
Latin Squares

Apr 26
2f Factorials

Apr 28
Homework 7 due
3f Factorials

May 1
Fractional Factorials

May 3
Confounding

May 5
Homework 8 due
Review

May 8
Exam 3

May 10
Review

May 12
Exam 4


 

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Managed by: Chris Edwards
edwards@uwosh.edu
Last updated February 5, 2006