Introduction to Categorical Data Analysis

Catalog description

Categorical data are among the most common data types encountered in social, health, biological, and data science fields. This course provides an introduction to the statistical analysis of categorical data. Topics include analysis of contingency tables, inference for proportions and odds ratios, logistic regression for binary and multi-category responses, and log-linear models for multi-way tables. Emphasis is placed on developing a strong theoretical foundation in generalized linear models for categorical outcomes. R will be used to supplement lectures with practical data analysis exercises. P: MATH 260 with at least a C grade. Fall Even.