This course requires as a prerequisite a grasp of basic statistical methods including linear models such as regression and ANOVA. Course content includes description and inference for binomial and multinomial observations using proportions and odds ratios; multiway contingency tables; generalized linear models for discrete data; logistic regression for binary responses; multi-category logit models for nominal and ordinal responses; inference for matched pairs and correlated clustered data; log linear models.

Prerequisite(s): STA 3024 or STA 3032 or STA 4210 or STA 4322.
Credit Hours: 3

View the full syllabus here (PDF)