When running Regression outputs or Generalized Linear Models, you may get a warning stating "Unusual observations detected." If that's the case, then you may have outliers in your data which are having an adverse effect on your model.

## Method

To automatically remove these outliers, take these steps:

1. Create and run your Regression output as usual (see Create Regression for more on the different types available).

2. If there are unusual observations in your data that may be caused by outliers, you'll get a warning, like this:

3. Select your regression output in the **report tree**, and copy/paste it. Work with the *copy* from here on.

4. Select the copy, and go to the settings for the regression analysis. Under **Inputs > Automated outlier removal percentage** specify a percentage limit for the removal of outliers.

5. Re-run the regression to see if removing the outliers made a difference to your outputs. If the model improved, then removing the outliers has been successful.

If the model still shows the warning after re-running it and removing outliers, then consider increasing the value. However, do note that the more outliers you remove, the less sample you'll have in your model which may result in other consequences.

## Next

How to Troubleshoot Regression Problems