Categorical Data Analysis

Catalog description

Prerequisite: MTH/STA 347 with a grade of “B” or better or departmental approval. The course will cover techniques of modeling data for data that are categorical rather than continuous in nature. Topics to be covered include joint, marginal, and conditional probabilities, relative risk, odds ratios, generalized linear models, logistic regression, multi-category logit models, and log linear models. The course will utilize data examples from the fields of biology, medicine, health, epidemiology, environmental science, and psychology. The course will use a statistical programming language. Counts toward the statistics minor; does not count toward the minor, BA or BS in Mathematics.