Overview
Description
Discrete distributions; inference for discrete and categorical responses; contingency tables; Chi-squared tests; generalized linear models; logistic regression, Poisson regression.
Requirements
Units
Lecture3
Catalog Details
Offering
Offered: Every Fall
Terms
fall
Attributes
Standard
Learning Outcomes
- 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).
- build, analyze, and interpret generalized linear models for categorical data, including multivariate logistic regression model with linear and nonlinear terms.
- perform categorical data analysis using professional statistical software and present results in technical reports and to professional audience.