When two or more predictors in a multiple linear regression model are highly correlated, it is known as __________.
- Autocorrelation
- Homoscedasticity
- Multicollinearity
- Overfitting
Multicollinearity is a phenomenon in which one predictor variable in a multiple regression model can be linearly predicted from the others with a substantial degree of accuracy. This can lead to unstable estimates of the coefficients.
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