Residual

Residuals are differences between the observed values and the corresponding values that are predicted by the model and thus represent the variance that is not explained by the model. The better the fit of the model, the smaller the values of residuals. The ith residual (ei) is equal to:

ei = (yi - yi-hat )

where

yi

is the ith observed value

yi-hat

is the corresponding predicted value

See also, Multiple Regression, Standard Residual Value, Mahalanobis Distance, Deleted Residual, and Cook's Distance.