In statistics, a situation in which two or more variables that serve as predictors of another variable are correlated to one another. Multicollinearity makes it difficult to determine the relative importance of each predictor on the dependent variable. For example, a researcher wishes to determine the effect of oil prices and weather on the demand for gasoline. Because oil prices are affected by weather, it is more difficult to determine the relative importance of each in its effect on the demand for gasoline.