Introduction to data analysis via linear models. Regression topics include estimation, inference, variable selection, diagnostics, remediation, and Ridge and Lasso regression. Course covers basic design of experiments and an introduction to generalized linear models. Matrix formulations are used. Data analysis in R and Python and effective written communication are emphasized.