Advanced Statistical Methods for Modern Data Analysis ((3 Units))

Catalog description

Prerequisites: Regression and ANOVA and statistical data management, or instructor's permission. This course provides exposure to a variety of advanced statistical methods (beyond the ones taught in our undergraduate curriculum) for handling the challenges of modern-day data analysis, along with their software implementation and applications. Topics include distribution-free statistical methods, modern regression methods (robust, penalized, nonparametric), generalized linear models, random effects models, generalized linear mixed models, generalized additive models, some machine learning methods, some data mining methods, graphical/network models and an introduction to biostatistics. (Formerly 3470:596)