You need to proceed with extreme caution when using a multiple regression model that has one or more large VIF values.

Question

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When a multiple regression model has one or more large VIF (Variance Inflation Factor) values, it indicates high multicollinearity among the independent variables. This means that the independent variables are highly correlated with each other, which can lead to incorrect coefficient estimates, reduced model reliability, and difficulty in interpreting the results. Therefore, it is important to proceed with caution and address the issue of multicollinearity before using such a model for analysis or prediction.

You Need to Proceed with Extreme Caution When Using a Multiple