Advanced Analytics

Continues introductions to intermediate and advanced statistical analysis methods for biomedical research. This course covers advanced regression topics, generalized linear models (GLM), generalized additive models (GAM), splines and smoothing techniques, decision trees, basic survival models, and introduces machine learning techniques (clustering, classification, regularization/penalized regression, feature selection, Bayesian methods, and unbiased estimators). Course content will be delivered through lectures and hands-on lab instruction.