The Variance Inflation Factor (VIF) is a statistical measure used to detect the presence of multicollinearity in a set of independent variables. In simpler terms, it quantifies how much the variance of a regression coefficient is inflated due to multicollinearity among the predictors. A high VIF indicates that an independent variable is highly correlated with one or more other variables, which could potentially distort the results of a regression analysis.
