Categorical Data Analysis (3 credits)
ASTAT 420


Description: Methods for analyzing categorical data are introduced, including those for contingency-table data (i.e., all variables are nominal or ordinal), as well as regression models for nominal and ordinal outcome variables. Although distribution theory and maximum likelihood are introduced as needed, the emphasis is on learning when and how to apply the methods, and how to interpret the results. Computations will be done either by hand or with the R computer program. Previous experience with R is useful, but not assumed.

Prerequisites: Introduction to Applied Statistics (or equivalent), and Intermediate Applied Statistics: Linear Models (or equivalent).