Collinearity is a phenomenon in which one attribute in a multiple linear regression model highly relates to another attribute in a multiple linear regression. An assessment of collinearity should be done to understand why some variables that an appraiser was expecting to be important in the model may not actually be significant.

It is important to know that collinearity does not reduce the ultimate predictive power of the model. It simply shifts most of the adjustment to one attribute over another.