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: DrDist, DrAccu, GIR, Sand Saves, Scrambling -----Step 2---- Coef -7264460 Constant DrDist DrAccu GIR Sand Saves Scrambling ------Step 1----- Coef P -11280801 12222 0.448 -58196 0.026 107488 0.008 48630 0.009 66373 0.114 S R-sq R-sq (adj) R-sq (pred) Mallows' Cp a to remove = 0.05 936403 21.64% 18.35% 12.93% 6.00 P -71841 0.000 121557 0.001 46404 0.012 58872 0.149 934761 13.60% 4.58 -----Step 3----- Coef -4296110 P 939054 14.14% 4.69 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 lowest multiple R-squared? The lowest adjusted R- squared? (Remember to briefly explain your answer.)