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Multiple regression. How to deal with Outliers and Colliniarity

When doing linear regression or multiple regression, your data may have outliers. Outliers are data points where the residual values are far from the model. In this video we explore how to identify outliers and discuss what to do when they are found. Colliniarity or multicolliniarity occurs when two or more of the explanatory variables are correlated. There are times when these variables should be kept in your model (when confounding is suspected for example).