Categorical Data Analysis

3 Credits · Level: Graduate, Undergraduate

This course covers theory and methods for the analysis of categorical data. The main subject areas are analysis of contingency tables, chi-square and exact tests, logistic models under binomial and multinomial sampling, log-linear models under Poisson sampling and their applications to perform contingency table analysis for nominal and ordinal variables. Methods of maximum likelihood estimation and goodness of fit procedures are discussed. Generalized linear model will be heavily utilized with an emphasis on model building and interpretation. Examples will be illustrated in R. Students are expected to use R or SAS when necessary, for all homework assignments.