D is c u s s th e p o te n tia l p ro b le m s o f m u ltic o llin e a r ity a nd s e ria l c o rre la tio n in th is tim e se ries d a ta a p p lic a tio n .

50. Revisit the introductory case, where we used the data labeled Baseball to estimate a multiple regression model as Examine the multicollinearity issue in this model.

51. Reconsider the estimated model, ŷ0 = 0.13 + 3.28x1 − 0.12 x2, where y, x 1, and x2 denote Win, BA, and ERA, respectively.

a. Construct the 95% prediction interval for Win if BA is 0.25 and ERA is 4.

b. Comment on any differences between this prediction interval and the confidence interval constructed in Example 15,7.