Regression Models

3 Credits · Level: Graduate, Undergraduate

This MS level course will focus on the theory and application of regression methods for statistical modeling and data analysis. Emphasis will be in the following areas: simple and multiple regression, inference and prediction, model building and diagnostics, model selection and validation, penalized regression (ridge, LASSO, elastic net), and selected topics in non-Gaussian and non-linear models. Practical issues involved in implementation of these methods will be presented using statistical software R based on example problems from a wide range of applications.