Multicollinearity is a statistical phenomenon in which two or more predictor variables in a regression model are highly correlated, meaning they contain similar information about the outcome variable. This can lead to unstable estimates of regression coefficients and can make it difficult to interpret the results of the model. What are consequences of multicollinearity? Multicollinearity … Read more