In multiple regression, the problem of multicollinearity affects the t-tests of the individual coefficients as well as the F-test in the analysis of variance for regression, since the F-test combines these t-tests into a single test.

Question

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Multicollinearity primarily affects the precision and interpretation of the individual regression coefficients (making their t-tests unreliable) but does not directly impact the F-test for the overall significance of the regression model. The F-test assesses whether at least one predictor variable has a non-zero coefficient, and it can still be significant even in the presence of multicollinearity.

In Multiple Regression, the Problem of Multicollinearity Affects the T-Tests