17. Screencast: Multicollinearity & VIFs

You saw in this video two different ways of identifying multicollinearity:

1. We can look at the correlation of each explanatory variable with each other explanatory variable (with a plot or the correlation coefficient).
   
   
2. We can look at Variance Inflation Factors (VIFs) for each variable. This calculation will be shown in more detail in the next video.

We saw that when x-variables are related to one another, we can have flipped relationships in our multiple linear regression models from what we would expect when looking at the bivariate linear regression relationships.

For more on VIFs and multicollinearity, here is the referenced post from the video on VIFs.