BST 5012 Statistical Methods I: Linear and Logistic Regression 3.0 Credits
The objective of this course is to provide students with a foundation of linear and generalized linear regression statistical frameworks (computation, theoretical properties, model interpretation, and application). Topics include review of basic concepts of matrix algebra that are particularly useful in linear and generalized linear regression and basic statistical programing features, (weighted) least square estimation, inference and testing, regression diagnostics, outlier influence, variable selection and robust regression, categorical response data and sampling methods, and two- and three-way contingency tables.
Repeat Status: Not repeatable for credit