Description
The regression model cannot solve (the design matrix cannot be inverted) in the presence of multicollinearity. Multicollinearity occurs when two or more variables are redundant (meaning that they are telling the same "story" or almost the same story). An effective model will have explanatory variables that each gets at a different facet of the dependent variable you are trying to predict/understand.