Office Boyd 313
Office Hours
M,W,F 11:00 – 12:00
MW 1:00 -3:30
Tu. 10:30 – 12:30
Text Applied
Linear Statistical Models 4th ed.
By John Neter, Michael Kutner, Chris
Nachtsheim, William Wasserman
Description
The purpose of this course is to learn when, why, and how
analysis of variance statistical testing is used. Random and fixed effects
ANOVA models will be studied extensively using the statistical software
Minitab. Multiple comparison methods such as Bonferroni, Scheffe, and
Tukey will be used.
Students will be able to apply the various ANOVA models
appropriately. (L7,L11)
Students will analyze ANOVA models to determine if they
satisfy the assumptions of valid models and give remedial measures if needed (L11)
Students will use the appropriate multiple comparison
method needed according to the information desired and analyze the results.(L7,L11)
Students will utilize residual analysis to detect
departures from ANOVA assumptions (L12)
Material Covered Chapters 16-21
Single factor ANOVA model
Estimation and testing of factor level effects
Tukey, Scheffe, and Bonferroni multiple comparison
procedures
Residual Analysis
Tests for constant variance
Overview of remedial measures
Two-Factor analysis of variance
Analysis of factor effects in two-factor studies
Two-factor studies-one case per treatment
Three Exams
60%
Project 20%
Final 20%
The project consists of 1 or more problems at the end of
each chapter that relate to a specific data set in the appendix. The problems
will be done on Minitab. These problems are applications of the material
covered in the chapter. The problems are to be kept in a folder and submitted
as a project. The project is due the
last class meeting.