Add the variables (HGT)2 and (AGE × HGT) to the data set for WGT, HGT, AGE, and (AGE)2 given in Section 16.3. Then, using an available regression program and the accompanying computer output, determine the best regression model relating WGT to the five independent variables as follows.
a. Use the forward approach.
b. Use the backward approach.
c. Use an approach that first determines the best model, employing HGT and AGE as the only candidate independent variables, and then determines whether any second-order terms should be added to the model. (Use α = .10.)
d. Compare and discuss the models obtained for each of the three approaches.
Regression Models for Dependent Variable: WGT
SSY = 888.25000, N = 12
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Number in Model R-Square C(p) MSE Variables in Model 0.7535 -0.4453 2189185 AGEHGT 0.6675 2.1916 29 53302 HGT2 0.6630 2.3295 29.93275 HGT 0.5926 4,4874 36.18571 AGE 0.5876 4.6413 36.63180 AGE2 0.7800 07440 21.71415 HGT AGE 0.77640.8535 22.06667 HGT AGE2 0.77550.88092215495 HGT AGEHGT 0.7731 0.9539 22.38984 AGE2 AGEHGT 0.7724 0976522 46250 AGE HGT2 0.7711 10152 22.58723 HGT2 AGEHGT 0.7677 206 22.92643 AGE2 HGT2 0.7669 1.1459 23.00799 AGE AGEHGT 0.6681 4.1729 3275423 HGT HGT2 0.5927 6.4844 40.19683 AGE AGE2 0.8028 2.0454 21.89768 HGT HGT2 AGEHGT 0.8002 2.1249 22 18565 HGT AGE2 HGT2 0.7959 2.2574 22.66559 HGT AGE HGT2 0.7803 2.7358 24.39869 HGT AGE AGE2 0.7802 2.7367 24.40178 HGT AGE AGEHGT 0.7769 28376 24.76744 AGE AGE2 AGEHGT 0.7764 28534 24.82438 HGT AGE2 AGEHGT 0.7739 29311 25.10614 AGE2 HGT2 AGEHGT 0.7734 2.9464 25.16136 AGE AGE2 HGT2 0.7725 2.9742 25.26208 AGE HGT2 AGEHGT 0.8043 40001 24.83873 HGT AGE HGT2 AGEHGT 0.8031 4.0344 24.98033トGTAGE2 HGT2 AGE-GT 0.8006 4.1127 25.30469 HGT AGE AGE2 HGT2 0.7803 4,7356 27.88308 HGT AGE AGE2 AGEHGT 0.7771 4833828.28980 AGE AGE2 HGT2 AGEHGT 5 0.8043 6.0000 28 97780 HGT AGE AGE2 HGT? AGEHGT