Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________. $$\begin{array} { | c | r | c | c | c | c | c | } \hline & y & x _ { 1 } & x _ { 2 } & x _ { 3 } & x _ { 4 } & x _ { 5 } \ \hline y & 1 & & & & & \ \hline x _ { 1 } & - 0.08301 & 1 & & & & \ \hline x _ { 2 } & 0.236745 & - 0.51728 & 1 & & & \ \hline x _ { 3 } & 0.155149 & - 0.22264 & - 0.00734 & 1 & & \ \hline x _ { 4 } & 0.022234 & - 0.58079 & 0.884216 & 0.131956 & 1 & \ \hline x _ { 5 } & 0.4808 & - 0.20467 & 0.078916 & 0.207477 & 0.103831 & 1 \ \hline \end{array}$$ A)x₁ and x₅ B)x₂ and x₃ C)x₄ and x₂ D)x₄ and x₃ E)x₄ and y

Question

Quizplus · Accepted Answer

The correlation coefficient between $x_2$ and $x_4$ is 0.884216, indicating a high degree of linear relationship, which suggests potential multicollinearity.

Inspection of the Following Table of Correlation Coefficients for Variables