How do you diagnose multicollinearity in a multiple linear regression model?
- By calculating the R-squared value
- By checking the correlation matrix and Variance Inflation Factor (VIF)
- By looking at the residual plot
- By looking at the scatter plot
Multicollinearity is diagnosed in a multiple linear regression model by checking the correlation matrix and the Variance Inflation Factor (VIF). A high correlation between independent variables and a VIF greater than 5 or 10 suggests the presence of multicollinearity.
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