This document provides an overview of statistical regression analysis with Python. It discusses defining assumptions, validating assumptions with a dataset on extramarital affairs, performing correlation analysis, estimating models using ordinary least squares, understanding regression results including interaction effects, handling categorical variables, and addressing outliers. Modeling techniques covered include linear, logistic, and quantile regression as well as robust linear regression.