# Interpretation of plots of residuals vs independent variables in multiple regression?

I know that to check the homoscedasticity assumption in OLS regression, we plot residuals vs predicted values. However, Excel provides plots of residuals vs each independent variable. What is the purpose of these graphs, what would be considered an abnormal finding, and what would we do about it?

• Unless I am misunderstanding (and please let me know if I am), I think this answer is wrong in its present form. The residual vector is not independent of the predictors. Under standard OLS and model assumptions you have $\mathbf{R} \sim \text{N}(\mathbf{0}, \sigma^2 (\mathbf{x}^\text{T} \mathbf{x})^{-1})$. This dependency means that it is preferable to use added-variable plots instead of comparisons of the residuals and individual predictors. Can you please review and correct if necessary, or let me know why I'm wrong. – Ben Feb 19 at 4:31