Question

The application of multiple regression analysis to a data set yields an F statistic that is highly significant and t ratios that are not significant. This is an indication that

(A) autocorrelation is present.
(B) multicollinearity is present.
(C) homoscedasticity is present.
(D) heteroscedasticity is present.

Answer 1

(B) multicollinearity is present.

Step-by-step explanation:

Multicollinearity -

It is the process where , one of the predictor variable in the multiple regression model can be linearly predicted from the others with the substantial degree of accuracy , is known as multicollinearity or collinearity .

In this case , the coefficient estimated of the multiple regression can change erratically for even a small change in the model .

hence , from the question , the indication is of (B) multicollinearity is present .