Golf.Imp Golf.imp Source EARNINGS SCORE DRIVE D DRIVE A PUTTS $239.493.68 70.37 288.4 60.2 31.824 $177,249.18 69.43 286.9 67.9 31.302 $218.619.18 70.23 276 71 31.806 $186,380.08 70.46 308.5 56.4 31.806 $209.511.75 69.78 262.9 60.5 31.428 $181,987 29 70.34 299. 1 52.7 31.716 $162.536.13 69.92 267.8 65.2 31.68 Columns (5/0) $174,534.95 70.25 277 62.4 31.518 $135,353.70 70.64 291.8 67.9 32.346 $212,540.82 69.93 294.2 61.3 31.554 EARNINGS 10 SCORE 11 $297,079.50 70.26 298.7 61.3 32.31 1 DRIVE_D 12 $168,904.45 69.96 291.4 64.8 31.788 DRIVE A 13 $135,791.58 70.21 309.8 55.7 31.734 PUTTS 14 $133,695.52 70.53 289.1 64.8 31.86 15 $112,192.04 70.59 279.7 71.2 31.302 16 $215,121.67 70.22 292.4 60.1 32.292 17 $183,922.93 70.86 287.2 52 31.986 18 $150,251.76 70.94 300 62.6 32.31 19 $183,356.69 71.13 291.7 67.1 32.058 20 $130,274.35 71.53 286.8 62.7 32.472 21 $286,285.40 69.73 308.4 70.6 32.094 22 $72,708.05 70.79 292.1 56.7 31.5 23 $99,597.31 71.07 295.8 57.2 31.518 24 $85,557.56 71.1 290.4 69,3 31.95 Rows All rows Selected Excluded Hidden LabeledDownload the file Golfimp, Use JMP to develop a multiple linear regression model to predict the Earnings/Event using the data found in Golfimp. Consider the four independent variables listed in the table below. Find the best model and check assumptions. y EARNINGS Average Earnings per Event X SCORE Average Score DRIVE D Average Drive Distance X3 DRIVE A Average Drive Accuracy X4 PUTTS Average Putts per Round [1] Create a correlation matrix for the variables EARNINGS, SCORE, DRIVE_D, DRIVE_A, and PUTTS using JMP. [2] What is the correlation coefficient for EARNINGS and SCORE? Interpret the linear relationship between the two variables. Correlation Coefficient Interpret the linear relationship[3] Does the correlation matrix indicate a potential multicollinearity problem? If so, which pair(s) of independent variables are a concern? If your answer is no, state why. Module 6 IMP Assignment Name Use IMP the fit the full model (all of the independent variables). Include the confidence interval and VIP for each of the regression parameters. Paste IMP output below. Include Summary of Fit, Analysis of Variance, and Parameter Estimates [4] Summ of Fit, Anal sis of Variance, and Parameter Estimates [5] State the null and alternative hypothesis statements for testing a multiple re ession modeL (F-test) [6] What is your conclusion about the overall model? [7] State the null and alternative hypothesis statements for testing the regression [8] What are your conclusions for each of the independent variables in the model? (Is the variable si_ icant or not) m Si ' icant at the 0.05 level? SCORE % Module 6 IMP Assignment Name [9] Is there a variable that should be removed from the multiple regression model? If so, which variable and why should it be removed? [10] Fit a new multiple regression model with the remaining independent variables. Summary of Fit, Analysis of Variance, and Parameter Estimates [11] What are your conclusions for each of the independent variables in the model? (Is the variable significant or not) Variable p - value Significant at the 0.05 level? [12] Is there a variable that should be removed from the multiple regression model? If so, which variable and why should it be removed?[13] Fit a new multiple regression model with the remaining independent variables. Summary of Fit, Analysis of Variance, and Parameter Estimates 3 Module 6 JMP Assignment Name [14] What are your conclusions for each of the independent variables in the model? (Is the variable significant or not) Variable p - value Significant at the 0.05 level? [15] Do the values of Variable Inflation Factors indicate any potential problems for this multiple regression? Why or why not?[16] State and interpret the Confidence Interval for the estimate of the regression coefficient of the independent variable SCORE. [17] What proportion of the variability of EARNINGS is explained by the multiple regression model. Interpret this value in terms of the problem. [18] Copy and paste the Residual by Predicted Plot [19] Describe the shape of the distribution. Does the residual by predicted plot support the assumption of constant variance? (Is there an extreme change in the variance?)[20] Use the multiple regression model to estimate the earnings per event for a golfer with an average score of 70 and an average of 32 putts per round. Compute a point estimate and construct a 95% Confidence Interval for the Mean. Interpret the confidence interval in terms of the problem. Point estimate Confidence Interval for the Mean Interpretation of the Confidence Interval for the Mean