BST 870 Generalized Linear Models 4.0 Credits
The objective of this course is to introduce students to generalized linear regression models (theoretical properties, model interpretation and application). Topics include: 1) Review of categorical data and related sampling distributions; 2) Two/Three-way contingency tables; 3) logistic regression and Poisson regression; 4) loglinear models for contingency tables; 5) generalized linear mixed models for categorical responses; 6) principles of MLE in generalized linear model.
Repeat Status: Not repeatable for credit
Prerequisites: BST 869 [Min Grade: B]