Scatter plot of residuals on the y axis and fitted values on the x axis to detect non-linearity, unequal error variances, and outliers.

## Arguments

- model
An object of class

`lm`

.- print_plot
logical; if

`TRUE`

, prints the plot else returns a plot object.

## Details

Characteristics of a well behaved residual vs fitted plot:

The residuals spread randomly around the 0 line indicating that the relationship is linear.

The residuals form an approximate horizontal band around the 0 line indicating homogeneity of error variance.

No one residual is visibly away from the random pattern of the residuals indicating that there are no outliers.

## See also

Other residual diagnostics:
`ols_plot_resid_box()`

,
`ols_plot_resid_hist()`

,
`ols_plot_resid_qq()`

,
`ols_test_correlation()`

,
`ols_test_normality()`

## Examples

```
model <- lm(mpg ~ disp + hp + wt, data = mtcars)
ols_plot_resid_fit(model)
```