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Question

What are the potential consequences of high

multicollinearity in a multiple regression model?

A Inflated standard errors and unreliable coefficient estimates

B Improved prediction accuracy and lower model variance

C No effect on the model’s R-squared or overall fit

D Higher significance of individual predictors and more accurate p-values

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