Modern Regression Methods

Catalog description

Students learn multiple linear regression, diagnostics for outliers and influential points, robust regression, quantile regression, collinearity, variable selection, ridge regression, the LASSO and elastic net, generalized linear models, and non-linear regression methods including generalized additive models and tree-based methods. Additional coursework is required for those enrolled in the graduate-level course.