We have already talked about this attribute for the conclusions of our model being reliable and sound that we should avoid multicollinearity between explanatory variables employed, and we should be sure that our explanatory variables prove to be independent among each other.

As we have discussed before, having variables too correlated within your set of explanatory variables could lead to our coefficient estimates being unreliable or unstable.

Two common ways to check for collinearity among variables is to compute the related value of tolerance and the variance inflation factor. I am not going to bore you again by discussing these two new concepts. Nevertheless, we are going to check for the assumption in a moment when actually estimating our model.