STAT 534 Applied Categorical Data Analysis
Introduction to analysis and interpretation of categorical data using analysis of variance or regression analogs. Topics may include contingency tables, generalized linear models, logistic regression, log-linear models, models for matching pairs, and modeling correlated and clustered responses; use of computer software such as SAS and R.
Credits
3
Prerequisite
STAT 201 or
STAT 216, or equivalent, or permission of department chair.