Case Study: Analysis of LPGA Tour Statistics The Ladies Professional Golf Association (LPGA) maintains data on performance for members of the LPGA Tour. Scoring average is generally considered the most important statistic in term of a player's success. To investigate the relationship between scoring average and variables such as driving distance, driving accuracy, greens in regulation, sand saves, and average putts per round, year-end performance data for 140 players on the LPGA Tour for 2012 are contained in the DATA file named TourLPGA2012 (LPGA website). Each row of the data set corresponds to a LPGA Tour player. Descriptions for the variables in the data set follow. Scoring Average: The average number of strokes per completed round. DrDist (Driving Distance): The average number of yards per measured drive. On the LPGA Tour driving distance is measured on two holes per round. Care is taken to select two holes which face in opposite directions to counteract the effect of wind. Drives are measured to the point at which they come to rest regardless of whether they are in the airway or not. . DrAccu (Driving Accuracy): The per e shot comes to rest in the fairway (regardless of club). Driving accuracy is measured on every hole, excluding par 3s. GIR (Greens in Regulation): The percentage of time a player was able to hit the green in regulation. A green is considered hit in regulation if any portion of the ball is touching the putting surface after the GIR stroke has been taken. The GIR stroke is determined by subtracting 2 from par (1st stroke on a par 3, and on a par 4, 3d on a par 5). In other words, a green is considered hit in regulation if the player has reached the putting surface in par minus two strokes. . Sand Saves: The percentage of time a player was able to get "up and down" once in a greenside sand bunker (regardless of score). "Up and down" indicates it took the player 2 shots or less to put the ball in the hole from a greenside sand bunker. PPR (Putts per Round): The average number of putts per round. Managerial Report Suppose that you have been hired by the commissioner of the LPGA to analyze the data for a presentation to be made at the annual LPGA Tour meeting. The commissioner has asked whether it would be possible to use these data to determine the performance measures that are the best predictors of a player's average score. Use the methods presented in this and previous chapters to analyze the data. Prepare a report that summarizes your analysis, including key statistical results, conclusions, and recommendations. Given Data Consider the complete data set, TourLPGA2012. Descriptive Statistics Compute the mean and standard deviation for each variable. (Round your answers to two decimal places.) Mean Standard Deviation Scoring Average Driving Distance Driving Accuracy Greens in Regulation Sand Saves Putts per Round Correlation Coefficients Using scoring average as the dependent variable, compute the sample correlation coefficients for each independent variable. (Round your answers to three decimal places.) Driving Distance (x1 ) Driving Accuracy (X2) Greens in Regulation (x}) Sand Saves (X) Putts per Round (x5) Comment on the correlation coefficients. The independent variable most highly correlated with the scoring average is [ ---Select-.. v ) . The independent variable least correlated with the scoring average is [-Select--- Using the single independent variable that is most highly correlated with the scoring average, develop an estimated regression equation. (Let x, represent driving distance, x, represent driving accuracy, x, represent greens in regulation, x, represent sand saves, and x represent putts per round. Round your coefficients to three decimal places.)Regression Analysis Use the backward elimination process to develop an estimated regression equation to predict scoring average using 0.05 for a-to-leave. (Let x, represent driving distance, x2 represent driving accuracy, x; represent greens in regulation, x, represent sand saves, and x, represent putts per round. Round your coefficients to three decimal places.) Compute R.2. (Round your answer to three decimal places.) Comment on the meaning of R. (Consider a proportion large if it is at least 0.55.) Since Ris [---Select-. v | 0.55, the estimated regression equation [---Select-. v a good fit