Which of the following statements describing the consequences of collinearity in a model is not true?
A) The value of the Variance Inflation Factor will be high.
B) An estimated coefficient may have an unexpected sign or size being large or small.
C) The F-statistic for the model may indicate overall significance, but most or all of the individual coefficients have t-statistics showing insignificance.
D) Collinearity occurs when two or more predictor variables are correlated.
E) When a predictor is collinear with the other predictors in the model, the standard error of its coefficient is always small and t-statistic always large.

Question

Quizplus · Accepted Answer

This statement is not true because collinearity can lead to inflated standard errors and reduced t-statistics for the collinear predictor variable. Therefore, the statement that the standard error of a collinear predictor is always small and its t-statistic always large is incorrect.

Which of the Following Statements Describing the Consequences of Collinearity