Mathematics 5803 Analysis of Variance

Professor Karen H. Smith

Office Boyd 313

Office Hours Mon. 10:00 11:00 1:00- 2:00

Tu. 12:15 3:15

Thur. 12:15 4:15

Text Applied Linear Statistical Models 5th ed.

By John Neter, Michael Kutner, Chris Nachtsheim, William Li



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.


Learning Outcomes


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


Topics Covered


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.