Linear Models and Advanced Regression Modeling. 3 credits

Catalog description

Presents a rigorous treatment of the theory of regression methodology and its applications. The course provides a geometric approach for univariate and multivariate regression models and covers maximum likelihood estimation, hypothesis tests, model selection, and regression diagnostics. Topics: matrix algebra for statisticians; Gauss-Markov theorem; inferences for linear models; theory of multiple regression and AOV; model assessment, selection and penalization; quantile regression and robust regression; random- and mixed-effects models. Offered by Statistics . May not be repeated for credit.