Course Homepage: Spring 2009

Usually Offered: Odd Numbered Springs

Purpose: To provide a rigorous analytical treatment of the theory and application of the analysis of variance based on the theory of the general linear statistical model.

Current Textbook: Theory and Application of the Linear Model, by F.A. Graybill, Duxbury, 1976.

 

Topics Covered	Chapters	Time
One-factor classification. Point estimation, confidence regions, and tests of hypothesis for the independent and constant variance case in the one-way layout; Simultaneous inferences; Orthogonal contrasts; Reparameterizations; Extensions to unbalanced data; Analysis of covariance.	12.1-12.4	3 weeks
Two-factor cross-classifications. Parameter estimation, tests of hypothesis, simultaneous inferences, tests for interaction, and reparameterizations for balanced data; Extensions to unbalanced data; No-interaction models; Randomized complete block designs.	13.1-13.5	7 weeks
Nested and general ANOVA models. Two-fold nested model; Three-factor models; General structure for balanced fixed-effects models.	14.1-14.4	2 weeks
Mixed effects models. Balanced mixed-effects models: estimation and inference, components of variance.	15.1-15.5	2 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: Joshua Tebbs
(Last Updated: July 11, 2008)