Categorical Data Analysis

Catalog description

This course is an introduction to categorical data analysis covering summaries and inference for categorical response and count data, analysis of contingency tables, generalized linear models for binary and count data, logistic regression, multicategory logit models, and log-linear models for contingency tables with an emphasis on applications and implementation using computer software. This course is taught largely at an undergraduate level. Graduate students have additional course requirements/expectations. Prerequisites: grade of "C" or better in STAT 305 or STAT 345 . Offered Fall - Even Numbered Years.