Regression Diagnostics
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# Regression Diagnostics ## 5.1 Residual Analysis **Residuals:** $e_i = y_i - \hat{y}_i$ ### Key Plots - **Residuals vs. fitted:** Should show random scatter (check homoscedasticity, linearity) - **QQ plot:** Check normality of residuals - **Residuals vs.

Regression Diagnostics
5.1 Residual Analysis
Residuals: ei=yi−y^i
Key Plots
- Residuals vs. fitted: Should show random scatter (check homoscedasticity, linearity)
- QQ plot: Check normality of residuals
- Residuals vs. order: Check independence
5.2 Influence Measures
- Leverage: hii — how far xi is from other x's
- Cook's distance: Di — influence of i-th observation on all fitted values
- DFFITS: Change in fitted values when observation i is deleted
Outlier Detection
- Standardized residuals >3 in absolute value
- Leverage >2(k+1)/n indicates high leverage
- Cook's distance >1 indicates high influence Join Discord PreviousANOVANextMulticollinearity