Regression Analysis Explained
Fit linear models, interpret coefficients and uncertainty, and verify assumptions using residual analysis.
📚 Fundamentals
- OLS: minimize sum of squared residuals
- Assumptions: linearity, independence, homoscedasticity, normality
- Diagnostics: residual plots, leverage, multicollinearity