Lets use multiple regression to predict total body weight (in pounds) using data from a study of

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Let€™s use multiple regression to predict total body weight (in pounds) using data from a study of University of Georgia female athletes. Possible predictors are HGT = height (in inches), % BF = percent body fat, and age. The display shows correlations among these explanatory variables.
Let€™s use multiple regression to predict total body weight (in

a. Which explanatory variable gives by itself the best predictions of weight? Explain.
b. With height as the sole predictor, = -106 + 3.65 (HGT) and r2 = 0.55. If you add %BF as a predictor, you know that R2 will be at least 0.55. Explain why.
c. When you add % body fat to the model, = -121 + 3.50(HGT) + 1.35(BF) and R2 = 0.66. When you add age to the model = - 97.7 + 3.43(HGT) + 1.36(BF) - 0.960(AGE) and R2 = 0.67. Once you know height and % body fat, does age seem to help you in predicting weight? Explain, based on comparing the R2 values.

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