STAT 653 - Categorical Data Analysis

(3 units)

Discrete distributions; inference for discrete and categorical responses; contingency tables; Chi-squared tests; generalized linear models; logistic regression, Poisson regression.

Prerequisite(s): STAT 352 or STAT 467 or STAT 667.

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Fall

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. perform statistical inference for categorical data organized in contingency tables (including odds ratio, Fisher test, Chi-square test, inference for proportions, multiway contingency tables, Cohran-Mantel-Haenszel test).
2. build, analyze, and interpret generalized linear models for categorical data, including multivariate logistic regression model with linear and nonlinear terms.
3. perform categorical data analysis using professional statistical software and present results in technical reports and to professional audience.

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