Regression & Statistical Models

Regression, generalized linear models, diagnostics, and model selection.

• Statistical modelling overview
• Simple linear regression
• Multiple linear regression
• Least squares and the geometry of regression
• Regression uncertainty and coefficient interpretation
• Linear-model assumptions and diagnostics
• Robust standard errors and robust regression
• Categorical predictors and contrasts
• Interaction terms and effect modification
• One-way and factorial ANOVA
• ANCOVA and regression-based ANOVA
• Logistic regression
• Odds ratios, probabilities, and calibration

Future notes in this level will cover Poisson and negative-binomial regression; generalized linear models; and model selection.

• Statistical Inference
• Advanced Modeling
• Statistics overview