F2PythonAdvancedAbout 180 min to complete
Multiple Regression
Simple regression (Notebook 44) explains an outcome with one predictor. But tips depend on bill size and party size and mealtime; body mass depends on flipper length and species and sex.
Notebook
About 180 minutes to complete
Enrol to read the notebook and download it to run.
What this module covers
Simple regression (Notebook 44) explains an outcome with one predictor. But tips depend on bill size and party size and mealtime; body mass depends on flipper length and species and sex.
By the end of it
- Fit and interpret a multiple regression — coefficients as effects holding other predictors constant
- Include categorical predictors via dummy coding (C(...)) and interpret their reference category
- Add and read interaction terms (when one predictor's effect depends on another)
- Use adjusted R² and know why it beats plain R² for comparing models
- Detect multicollinearity with the Variance Inflation Factor (VIF) and understand its damage
- Compare models with nested F-tests and information criteria (AIC/BIC)
- Check diagnostics and influential points in the multivariable setting, and predict from the model