Refer to the SENIC data set in Appendix C.1 and Project 9.25. The regression model identified as best in Project 9.25 is to be validated by means of the validation data set consisting of cases 1-56. a. Fit the regression model identified in Project 9.25 as best to the validation data set. Compare the estimated regression coefficients and their estimated standard deviations with those ob- tained in Project 9.25. Also compare the error mean squares and coefficients of multiple determination. Does the model fitted to the validation data set yield similar estimates as the model fitted to the model-building data set? b. Calculate the mean squared prediction error in (9.20) and compare it to MSE obtained from the model-building data set. Is there evidence of a substantial bias problem in MSE here? c. Combine the model-building and validation data sets and fit the selected regression model to the combined data. Are the estimated regression coefficients and their estimated standard deviations appreciably different from those for the model-building data set? Should you expect any differences in the estimates? Explain.