Residual Rechner — Formel
## Regression Residuals
A residual is the difference between an observed value and its predicted value from the regression model. Residuals are the foundation for assessing model fit and detecting problems.
### Formula
**e_i = y_i - y-hat_i**
Positive residuals mean the model under-predicted; negative residuals mean over-prediction. In a well-fitting model, residuals should be randomly scattered around zero with no patterns.
A residual is the difference between an observed value and its predicted value from the regression model. Residuals are the foundation for assessing model fit and detecting problems.
### Formula
**e_i = y_i - y-hat_i**
Positive residuals mean the model under-predicted; negative residuals mean over-prediction. In a well-fitting model, residuals should be randomly scattered around zero with no patterns.
Lösungsbeispiel
An observation with actual y = 25 and predicted y-hat = 23.5.
- Residual = 25 - 23.5 = 1.5
- The model under-predicted by 1.5 units.
- Squared residual = 1.5² = 2.25