Graph for identifying outliers.

## Arguments

- model
An object of class

`lm`

.- threshold
Threshold for detecting outliers. Default is 3.

- print_plot
logical; if

`TRUE`

, prints the plot else returns a plot object.

## Value

`ols_plot_resid_stud`

returns a list containing the
following components:

- outliers
a

`data.frame`

with observation number and`studentized residuals`

that exceed`threshold`

for classifying an observation as an outlier

- threshold
`threshold`

for classifying an observation as an outlier

## Details

Studentized deleted residuals (or externally studentized residuals) is the deleted residual divided by its estimated standard deviation. Studentized residuals are going to be more effective for detecting outlying Y observations than standardized residuals. If an observation has an externally studentized residual that is larger than 3 (in absolute value) we can call it an outlier.

## Examples

```
model <- lm(mpg ~ disp + hp + wt, data = mtcars)
ols_plot_resid_stud(model)
ols_plot_resid_stud(model, threshold = 2)
```