BIOS 642 — Health Data: Statistical Learning and Model Visualization

Basic principles of regression analyses applicable to the health sciences, covering regression (linear and generalized linear models) and inference for regression parameters; confounding, effect modification, and collinearity; model selection; prediction; and visual representations of model output, covariate-response relationships, and prediction curves.

• Credits: 3
• Faculty: Graduate Studies
• Department: Epidemiology and Biostatistics
• Prerequisites: BIOS 641