Syllabus

Instructor

Spring 2008 Office Hours:

Class Meeting Time

Textbook:
Required Textbook: "Applied Linear Statistical Models" (5th edition) by Kutner, Nachtsheim, Neter, and Li.
(This is the same book used for STAT 704 in the fall.)

Supplementary Books (NOT required):
"Linear Models with R" by Faraway, J.J.
"Extending the Linear Model with R" by Faraway, J.J.
"An R and S-plus Companion to Applied Regression" by Fox, J.
"Statistical Analysis and Data Display" by Heiberger and Holland.
"Statistical Research Methods in the Life Sciences" by Rao, P.V.

Computer Code for Class Examples

Statistical Topic	Example in SAS Code	Example in R Code
Regression with Qualitative Predictors	SAS example: (Insurance Innovation data & Shirt data)	R example: (Insurance Innovation data & Shirt data)
Single-Factor ANOVA	SAS example: (Kenton Foods data)	R example: (Kenton Foods data)
Regression Approach to ANOVA model	SAS example: (Kenton Foods data)	R example: (Kenton Foods data)
Investigation of Treatment Means	SAS example: (Kenton Foods data)	R example: (Kenton Foods data)
Checking ANOVA Model Assumptions	SAS example: (Kenton Foods data)	R example: (Kenton Foods data)
Two-Factor ANOVA	SAS example: (Castle Bakery data)	R example: (Castle Bakery data)
Investigation of Factor Effects (No Interaction)	SAS example: (Castle Bakery data)	R example: (Castle Bakery data)
Investigation of Factor Effects (With Interaction)	SAS example: (Melon data)	R example: (Melon data)
Two-Factor ANOVA With One Observation per Cell	SAS example: (Insurance data)	R example: (Insurance data)
Two-Factor ANOVA With Unequal Cell Sample Sizes	SAS example: (Growth data) (SAS example includes empty-cell analysis)	R example: (Growth data)
Three-Factor ANOVA	SAS example: (stress data)	R example: (stress data)
Random-Effects Model	SAS example: (Apex Enterprises data)	R example: (Apex Enterprises data)
Mixed-Effects Model	SAS example: (training data)	R example: (training data)
Randomized Complete Block Design	SAS example: (executive data)	R example: (executive data)
Generalized Random Block Design	SAS example: (task completion data)	R example: (task completion data)
Balanced Incomplete Block Design	SAS example: (taste test data)	R example: (taste test data)
Latin Square Design	SAS example: (bank teller data)	R example: (bank teller data)
Single-Factor Repeated Measures	SAS example: (wine judging data)	R example: (wine judging data)
Analysis of Covariance	SAS example: (cracker data)	R example: (cracker data)
Piecewise Regression	SAS example: (raw materials data)	R example: (raw materials data)
Nested Design	SAS example: (training school data)	R example: (training school data)
1 × 2 Contingency Tables (Inference about binomial probability) (z-test/CI and Binomial test)	SAS example: (driver's test data)	R example: (driver's test data)
1 × c Contingency Tables (Inference about multinomial probabilities) (Chi-square goodness-of-fit test)	SAS example: (blood types data)	R example: (blood types data)
2 × 2 Contingency Tables (Comparing 2 proportions, independent samples) (z-test/CI and Fisher's Exact test)	SAS example: (trees data)	R example: (trees data)
2 × 2 Contingency Tables (Comparing 2 proportions, paired samples) (McNemar's test)	SAS example: (ice cream data)	R example: (ice cream data)
r × c Contingency Tables (Chi-square test for independence & Chi-square test for homogeneity)	SAS example: (snoring data & voter data)	R example: (snoring data & voter data)
Distribution-free Tests in ANOVA (Kruskal-Wallis Test & multiple comparisons)	SAS example: (soil data)	R example: (soil data)
Distribution-free Tests for RCBD (Friedman Test)	SAS example: (wind speed data)	R example: (wind speed data)

Available Computing Resources: R is available as a free download from the CRAN home page) and students who want SAS can buy a copy from USC Computer Services.
These packages are also available on the computers in the labs in LeConte College (and a few other buildings). Help in using R can be found on the CRAN home page.

Downloading Instructions for R

• Instructions for Downloading R

Computing Tips: Some Review

• Introduction to SAS which should be a good instruction for the software

Homework

• Homework 1 (due Wednesday, January 23)

• Homework 2 (due Monday, February 4)

• Homework 3 (due Wednesday, February 13)

• Homework 4 (due Friday, February 29)

• Homework 5 (due Monday, March 24, although I will accept it March 25)

• Homework 6 (due Tuesday, April 15)

• Homework 7 (due Thursday, April 24 by 4:30 p.m.)

Data Sets

• Insurance Innovation Data Set (from Chapter 8)

• Shirt Data Set

• Kenton Foods Data Set (from Chapter 16)

• Copier Maintenance Data Set

• Questionnaire Color Data Set

• Rehabilitation Therapy Data Set

• Castle Bakery Data Set (from Chapter 19)

• Melon Data Set

• Insurance Data Set (from Chapter 20)

• Growth Data Set (from Chapter 23)

• Stress Data Set (from Chapter 24)

• Apex Enterprises Data Set (from Chapter 25)

• Training Data Set (not the same data as in the book's example!)

• Eye Contact Data Set

• Programmer Requirements Data Set

• Coin-operated Terminals Data Set

• Adjunct Professors Data Set

• Case Hardening Data Set

• Sodium Content Data Set

• Imitation Pearls Data Set

• Executive Data Set (from Chapter 21)

• Task Completion Data Set (from Chapter 21)

• Auditor Training Data Set

• Auditor Training (Problem #21.13) Data Set

• Automobile Tire Wear Data Set

• Hardware Sales Data Set

• Taste Test Data Set (from Chapter 28)

• Bank Teller Data Set (from Chapter 28)

• Wine Judging Data Set (from Chapter 27)

• Cracker Data Set (from Chapter 22)

• Training School Data Set (from Chapter 26)

• Questionnaire Color #22.9 Data Set

• Bottling Plant Production Data Set

• Muscle Mass Data Set

Review Sheets

• Test 1 Review Sheet

• Test 2 Review Sheet

• Test 3 Review Sheet (also see review sheets for Tests 1 and 2)

Formula Sheets

• Test 1 Formula Sheet (No need to bring this to the test --- a copy will be provided with your test.)

• Test 2 Formula Sheet (No need to bring this to the test --- a copy (without the ugly "line"!) will be provided with your test.)

• The final exam will be cumulative. Many of the questions will cover material after Test 2.
  You will be allowed to bring one standard-sized sheet of paper to the final exam with anything written on it (front and back).
  In addition, the final exam will include the formula sheets from Tests 1 and 2.

Information about the Project

• Information about the Spring 2008 STAT 705 project

• STAT 705 Project Grading Guidelines

Exams

• Exam 1: Feb. 22
• Exam 2: March 28
• Final Exam (Thursday, May 1, 2:00 p.m.)