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.

General Education

Offered

  • Fall