13.88 R can’t go down The least squares prediction equation provides predicted values yn with the strongest possible correlation with y out of all possible prediction equations of that form. Based on this property, explain why the multiple correlation R cannot decrease when you add a variable to a multiple regression model. (Hint: The prediction equation for the simpler model is a special case of a prediction equation for the full model that has coefficient 0 for the added variable.)