Michael Grogan shows how you can find and re-weigh outliers when performing regressions:
A useful way of dealing with outliers is by running a robust regression, or a regression that adjusts the weights assigned to each observation in order to reduce the skew resulting from the outliers.
In this particular example, we will build a regression to analyse internet usage in megabytes across different observations. You will see that we have several outliers in this dataset. Specifically, we have three incidences where internet consumption is vastly higher than other observations in the dataset.
Let’s see how we can use a robust regression to mitigate for these outliers.
Click through for a demonstration.