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STAT 574C - Categorical Data Analysis
Description: Analysis of contingency tables. Generalized Linear Models including logistic regression and log-linear models. Matched-pair models. Repeated categorical responses. Students will be expected to utilize standard statistical software packages for computational purposes.
Prerequisite(s): STAT 571A/MATH 571A, or equivalent.
This course in Categorical Data Analysis studies data analytic methods for discreet data representing categorical outcomes. It is targeted to provide graduate students in statistics and in subject-matter fields with experience in description and statistical inference for contingency table data, to extend expertise in constructing and interpreting models for discrete response data, and to develop expertise in constructing and interpreting log-linear and other generalized linear models for categorical data.
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