Explanation:
Option D is correct because the correlation matrix shows extremely high correlations between the independent variables:
These high correlations indicate multicollinearity, which occurs when independent variables in a regression model are highly correlated with each other. This explains why we have:
Why other options are incorrect:
Option A: The coefficient of 0.3533 for Russell 3000 has a p-value of 0.8382, which is not statistically significant (p > 0.05).
Option B: High R² doesn't guarantee that individual coefficients are statistically significant. Here, all coefficients have high p-values (> 0.05).
Option C: A high p-value (0.9452) indicates the coefficient is NOT statistically significant, not more significant.
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Based on the regression results, which statement is correct?
A
The estimated coefficient of 0.3533 indicates that the returns of the Russell 3000 index are more statistically significant in determining the portfolio returns than the other two indexes.
B
The high adjusted R² indicates that the estimated coefficients on the Russell 1000, Russell 2000, and Russell 3000 indexes are statistically significant.
C
The high p-value of 0.9452 indicates that the regression coefficient of the returns of Russell 1000 is more statistically significant than the other two indexes.
D
The high correlations between each pair of index returns indicate that multicollinearity exists between the variables in this regression.