Question: a) Generate correlation table for the 12 numerical predictors and search for highly correlated pairs. These have potential redundancy and can cause multicollinearity. If we

a) Generate correlation table for the 12 numerical predictors and search for highly correlated pairs. These have potential redundancy and can cause multicollinearity. If we decide that those variables with the 3 lowest correlation scores with MEDV and the variable that is most correlated with other variables should be removed, which variables would those be?

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