1. (Supplemental Exercise - Required) For a recent season, several variables were recorded for 125 professional golfers. We are interested in using multiple regression to predict Earnings ($) from the predictors indicated in the backward elimination output (with some deletions) below. Briefly explain your answers. Regression Analysis: Earnings ($) versus DrDist. DrAccu, GIR, Sand Saves, Scrambling Backward Elimination of Terms Candidate terms: DER DEACCUGIR, Sand Saves, Scrambling -----Step 2 ----- Coef P -7264460 -----Step 3----- Seer -4296110 Constant Dist Dracow GIR Sand Saves Scrambling ----Step 1 ----- Ceef P -11280801 12222 0.448 -58196 0.026 107488 0.008 48630 0.009 66373 0.114 -71841 1:1557 1 46404 58872 0.000 0.001 0.012 0.149 S 934761 939054 R- R-agladih R-1 (Busch Mallows' Se 936403 21.648 18.35% 12.938 6.00 13.606 4.58 14.14% 4.69 a to remove = 0.05 a. Step 3 produces the final model. Which of the predictor(s) will not be in it? (Remember to briefly explain your answer.) b. Which of the models has the highest multiple R-squared? The highest adjusted R- squared? (Remember to briefly explain your answer.) 2. (Supplemental Exercise - Required) Refer again to the data above. Not satisfied with these predictors, we add a predictor to our dataset called Bounce Back. Below is Best Subsets output using this new dataset. Briefly explain your answers. Best Subsets Regression: Earnings ($) versus DrDist, DrAccu, ... Response is Earnings ($) SS a cu nrn dac DD me Sb DA al B cova R-Saatana SCInc (Rxed) CR SURA9k 5.0 Dian222222 X 11.1 9.9 960722 X 14.1 5.1 939054 XXX 13.6 5.0 930761 X X X X 13.1 5.2 931759 X X X X X 12.2 Bul222 X X X X X X R-S Vacab-se cads) 1 8.1 7.4 Ambient 14.1 a122 17.9 Inand 19.6 22 19.1 6 22.6 18.6 a. Based on this output, the predictor with the highest correlation in absolute value with Earnings is (Remember to briefly explain your answer.) The absolute value of its correlation with Earnings is b. By the criterion of Best Subsets Regression, the best model for this dataset uses which predictors? (Remember to briefly explain your answer) c. TRUE or FALSE: The model, Earnings vs. Debiu, Sand Saves, and Bounce Back, will have a multiple R-squared less than 15.4%. 1 d. TRUE or FALSE: The model, Earnings vs. DtDixt, Sand Saves, and Bounce Back, will have an adjusted R-squared less than 14.1%. 1. (Supplemental Exercise - Required) For a recent season, several variables were recorded for 125 professional golfers. We are interested in using multiple regression to predict Earnings ($) from the predictors indicated in the backward elimination output (with some deletions) below. Briefly explain your answers. Regression Analysis: Earnings ($) versus DrDist. DrAccu, GIR, Sand Saves, Scrambling Backward Elimination of Terms Candidate terms: DER DEACCUGIR, Sand Saves, Scrambling -----Step 2 ----- Coef P -7264460 -----Step 3----- Seer -4296110 Constant Dist Dracow GIR Sand Saves Scrambling ----Step 1 ----- Ceef P -11280801 12222 0.448 -58196 0.026 107488 0.008 48630 0.009 66373 0.114 -71841 1:1557 1 46404 58872 0.000 0.001 0.012 0.149 S 934761 939054 R- R-agladih R-1 (Busch Mallows' Se 936403 21.648 18.35% 12.938 6.00 13.606 4.58 14.14% 4.69 a to remove = 0.05 a. Step 3 produces the final model. Which of the predictor(s) will not be in it? (Remember to briefly explain your answer.) b. Which of the models has the highest multiple R-squared? The highest adjusted R- squared? (Remember to briefly explain your answer.) 2. (Supplemental Exercise - Required) Refer again to the data above. Not satisfied with these predictors, we add a predictor to our dataset called Bounce Back. Below is Best Subsets output using this new dataset. Briefly explain your answers. Best Subsets Regression: Earnings ($) versus DrDist, DrAccu, ... Response is Earnings ($) SS a cu nrn dac DD me Sb DA al B cova R-Saatana SCInc (Rxed) CR SURA9k 5.0 Dian222222 X 11.1 9.9 960722 X 14.1 5.1 939054 XXX 13.6 5.0 930761 X X X X 13.1 5.2 931759 X X X X X 12.2 Bul222 X X X X X X R-S Vacab-se cads) 1 8.1 7.4 Ambient 14.1 a122 17.9 Inand 19.6 22 19.1 6 22.6 18.6 a. Based on this output, the predictor with the highest correlation in absolute value with Earnings is (Remember to briefly explain your answer.) The absolute value of its correlation with Earnings is b. By the criterion of Best Subsets Regression, the best model for this dataset uses which predictors? (Remember to briefly explain your answer) c. TRUE or FALSE: The model, Earnings vs. Debiu, Sand Saves, and Bounce Back, will have a multiple R-squared less than 15.4%. 1 d. TRUE or FALSE: The model, Earnings vs. DtDixt, Sand Saves, and Bounce Back, will have an adjusted R-squared less than 14.1%