In the following regression, which statement best describes the degree of multicollinearity? $\begin{array}{lrrrrr}
\hline \text { Variables } & \text { Coefficients } & \text { Std. Error } & t(d f=81) & p \text {-value } & \text { VFF } \
\hline \text { Intercept } & 9.8080 & 16.9900 & 0.577 & 5654 & \
\text { NumCyl } & -1.6804 & 0.5757 & -2.919 & 0045 & 3.159 \
\text { HPMax } & -0.0369 & 0.0140 & -2.630 & 0102 & 3.068 \
\text { ManTran } & 0.2868 & 1.2802 & 0.224 & 8233 & 2.105 \
\text { Length } & 0.1109 & 0.0601 & 1.845 & 0686 & 4.339 \
\text { Wheelbase } & -0.0701 & 0.1714 & -0.409 & 6836 & 7.553 \
\text { Width } & 0.4079 & 0.2922 & 1.396 & 1665 & 6.857 \
\text { RearStRm } & -0.0085 & 0.2018 & -0.042 & 9666 & 2.015 \
\text { Weight } & -0.0025 & 0.0020 & -1.266 & 2090 & 7.670 \
\text { Domestic } & -1.2291 & 1.1391 & -1.079 & 2838 & 1.825 \
\hline
\end{array}$
A)Very little evidence of multicollinearity.
B)Much evidence of multicollinearity.
C)Only NumCyl and HPMax are collinear.
D)Only ManTran and RearStRm are collinear.

Question

Quizplus · Accepted Answer

The VIF (Variance Inflation Factor) values for several variables are significantly above the common threshold of 5, indicating a high degree of multicollinearity among the predictors in the model.

In the Following Regression, Which Statement Best Describes the Degree