Multicollinearity vs. Autocorrelation: What's the Difference?
Multicollinearity and Autocorrelation Definitions
Multicollinearity
(statistics) A phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, so that the coefficient estimates may change erratically in response to small changes in the model or data.
Autocorrelation
The cross-correlation of a signal with itself: the correlation between values of a signal in successive time periods.
Multicollinearity
A case of multiple regression in which the predictor variables are themselves highly correlated
