Multicollinearity affects the t-tests of the individual coefficients as well as the F-test in the analysis of variance for regression because the F-test combines the t-tests into a single test.

Question

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Multicollinearity primarily affects the reliability and interpretation of the individual coefficients' t-tests by inflating their variances, making it harder to determine their individual significance. However, the F-test, which assesses the overall significance of the regression model, remains unaffected by multicollinearity because it evaluates the model as a whole, not the individual predictors.

Multicollinearity Affects the T-Tests of the Individual Coefficients as Well