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Comment on the correlation coefficients. The independent variable most highly correlated with the scoring average is ---Select--- ---Select-- The independent variable least correlated with the scoring average is Using the single independent variable that is most highly correlated with the scoring average, develop an estimated regression equation. (Let x, represent driving distance, x₂ represent driving accuracy, x, represent greens in regulation, x4 represent sand saves, and x, represent putts per round. Round your coefficients to three decimal places.) 9- 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.) y = 61.55707609 Compute R₂2. (Round your answer to three decimal places.) 0.962 Comment on the meaning of R.2. (Consider a proportion large if it is at least 0.55.) Since R₂2 is greater than 0.55, the estimated regression equation provides a good fit.

Comment on the correlation coefficients. The independent variable most highly correlated with the scoring average is ---Select--- ---Select-- The independent variable least correlated with the scoring average is Using the single independent variable that is most highly correlated with the scoring average, develop an estimated regression equation. (Let x, represent driving distance, x₂ represent driving accuracy, x, represent greens in regulation, x4 represent sand saves, and x, represent putts per round. Round your coefficients to three decimal places.) 9- 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.) y = 61.55707609 Compute R₂2. (Round your answer to three decimal places.) 0.962 Comment on the meaning of R.2. (Consider a proportion large if it is at least 0.55.) Since R₂2 is greater than 0.55, the estimated regression equation provides a good fit.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Scoring Average DrDist DrAccu GIR Sand Saves PPR
74.160 247.280 72.9 61.1 35.7 30.76
75.333 252.121 68.1 64.5 23.5 31.88
74.108 250.737 58.9 65.2 45.1 31.47
73.466 247.000 70.7 62.2 42.9 30.04
73.174 251.565 73.6 67.2 34 30.96
75.895 247.368 62.6 56.4 38.1 31.26
73.282 254.282 70.1 65.2 46 30.74
72.415 247.585 71.8 68.4 46.3 30.37
73.743 263.286 67.7 64.9 32.5 31.00
73.622 249.676 60.2 61.6 36.6 29.92
71.634 246.317 74.7 70.8 37.9 30.13
70.488 254.070 74.9 72.7 45.6 29.50
75.000 263.649 60.1 64.9 37.5 32.14
73.176 248.971 67.7 65.4 53.5 30.68
72.233 239.571 73.3 63.8 49 29.07
70.952 245.257 79 72.9 56.9 30.01
74.071 257.697 54.7 58.3 41.7 30.03
76.278 232.857 65.1 53.2 32.1 30.56
73.436 239.256 57.1 60.8 39.6 30.21
74.519 262.556 69 65.8 44.8 31.52
74.379 224.517 79.6 55.9 34.1 29.66
72.514 252.800 73.2 66.7 48.1 30.26
74.629 246.118 69.3 60.5 21.7 31.17
72.725 258.304 71.2 68.2 40.3 30.60
74.351 257.919 69.3 66.8 44.8 32.18
70.841 256.344 76.8 73 39.1 30.16
74.667 258.139 62.6 66.2 29.3 31.94
74.368 237.395 77.2 62.6 37 30.71
72.868 246.364 69.1 64.9 36.5 30.25
71.802 259.783 66.3 67.4 42 29.86
71.965 240.711 76.8 65.8 50.8 29.46
74.556 254.037 71.8 65.8 36 32.19
72.271 251.311 73.9 71.1 42.4 30.20
73.723 244.047 71.1 60.9 47.6 30.12
73.279 263.050 67.1 65.8 44.9 30.65
72.571 247.595 71.1 68.5 47.1 30.09
72.333 249.408 72.7 67.7 46.4 30.26
73.030 234.879 82.7 66.3 37.8 30.73
72.268 252.333 69.3 69.6 32.1 30.49
73.706 243.758 75.8 68 48 31.74
73.559 266.961 61.2 66.5 39 30.87
72.437 253.382 70 66.7 39.4 29.79
74.679 242.233 65.4 58.5 52.6 30.44
72.286 262.159 58.2 64.8 59.7 29.16
74.400 248.862 59.7 59 35.6 30.00
72.952 262.622 65 67.4 34.8 30.42
71.104 246.676 73.4 72.4 46.7 30.11
72.813 240.719 74.8 59.1 37.5 28.58
72.684 241.507 76.6 68.9 46.3 30.42
74.093 240.239 63 63.8 42.2 30.83
72.064 247.865 76.8 68.4 38.3 30.15
73.296 250.741 69.1 64.4 40.6 30.44
74.211 243.459 69.2 62 38.5 30.95
72.393 246.934 73.6 66 40.5 29.96
71.537 254.638 68.4 66.8 41.5 29.11
73.754 243.979 72 65.6 48.1 31.07
74.679 240.679 62.4 57.7 40.5 30.32
71.272 258.563 74.6 70.6 37.8 29.93
74.019 237.341 78 63.4 36.4 30.68
71.306 241.984 75.6 70.4 51.8 29.65
73.035 249.854 72.8 68.8 37.5 30.80
76.864 251.235 46.2 47.7 24.1 29.35
76.964 232.464 59.7 48.8 35.8 30.46
72.938 262.785 65 69.2 34.9 30.96
72.134 242.417 76.2 69.9 50.8 30.07
72.900 246.338 75.6 66 39.3 30.23
71.589 261.939 68.3 71.8 51.4 30.32
72.384 243.219 74 65.2 52.2 30.03
72.350 260.475 63.1 65.7 52.1 30.08
74.019 243.887 68 61.8 42.6 30.08
72.239 233.900 77.9 66.3 44.6 29.51
74.250 245.139 71.7 59.1 34.6 30.33
73.783 252.696 72.3 62.3 22.2 30.61
70.333 260.036 74.8 75.2 41.5 29.78
71.525 276.083 64 71.3 53.5 30.28
72.600 252.018 66.8 64.9 40.4 29.47
73.056 219.944 82.4 58.3 66.7 29.19
73.861 231.361 77.9 60.2 39.3 29.97
73.525 254.078 72 65 46 30.68
72.943 230.765 83.9 64.7 34 30.35
71.088 255.603 69.2 70.2 44.9 29.66
73.551 243.115 73.2 66.3 19.7 31.21
72.484 259.983 64.8 66.8 48 29.84
74.636 243.091 61.9 62.8 46.3 31.33
70.564 242.881 79.3 68.3 50 28.68
70.939 240.679 84.8 71.9 26.5 29.69
74.000 248.389 67.7 67.7 34.2 31.78
73.266 239.613 72.4 65.1 43.5 30.38
72.643 251.894 71.4 65.3 42.3 30.23
70.898 255.663 70.5 74.1 47.2 29.76
71.189 248.448 72.9 71.8 43.5 29.95
74.375 241.450 71.9 58.9 33.3 30.05
73.250 239.295 77 64.8 41.3 31.09
74.302 254.814 64.3 63.7 27.6 30.93
73.395 249.256 62.2 59.2 38.3 29.40
71.184 259.500 62.5 70 53.3 29.44
71.706 256.189 69.4 70 45.1 30.13
70.212 254.840 73.4 68.9 45.9 28.34
73.349 242.366 74 66 34.4 31.00
70.744 265.385 71 72.8 52.9 30.30
72.429 247.197 74.2 66.3 44.3 30.24
72.560 268.932 64.1 66 37.3 30.36
73.680 244.840 65.9 61.8 48.6 30.16
73.647 242.119 69.7 60.1 58 28.43
74.171 238.900 80.5 61 52.5 30.51
73.067 243.111 75.7 65.4 36.4 30.51
71.687 244.191 80.1 72.5 38.6 30.51
73.583 246.917 74.4 64.6 18.2 30.83
72.171 248.756 74.2 69.4 30.8 30.49
70.302 258.200 73.3 71.7 39.7 29.25
71.719 249.953 74.9 69.7 35.7 29.77
72.972 251.646 67 64.9 46.3 29.71
71.571 251.135 72.8 66.2 54.8 29.25
72.632 257.567 64.4 66.6 35.7 30.24
75.429 247.286 60.8 57.9 37.8 30.79
72.900 262.900 67.5 65 35.4 30.45
73.885 249.538 69.2 63.5 32 30.65
75.217 236.545 73.5 52.4 40.5 29.48
72.060 243.096 75.4 68.4 50.9 30.03
70.308 242.145 83.5 73.7 59.4 29.51
72.093 264.573 71.3 76.1 26.3 31.41
72.772 253.491 66.8 66.3 28.8 30.47
74.605 231.919 75.6 60.1 37 30.79
73.188 243.750 71.8 64.1 45.5 29.91
71.506 255.141 72.9 70 31.6 29.78
73.017 257.898 64.3 67.2 29.8 30.57
73.043 250.413 69.4 66.8 31.9 30.53
73.897 245.026 49.9 59.4 45.9 30.00
71.568 271.973 69.2 72.5 45.3 30.98
71.122 266.986 58.5 68.8 41.7 29.53
71.850 246.392 72.8 66.7 43.6 30.00
72.034 258.814 69.7 67.7 46.3 30.06
72.592 258.282 63.8 67.3 44.3 30.15
73.271 248.500 67.7 66.7 43.2 31.05
71.192 259.000 73.8 72.3 38.9 30.18
73.485 268.589 53 66 39.7 31.16
72.211 241.909 76.5 66 57.9 29.75
71.040 258.046 69 70.7 42.9 29.71
71.659 256.667 74.2 75.2 53.6 30.98
73.829 252.324 67.5 61 41.1 30.26
Multiple R 0.980765 R Square 0.9619 Adjusted F 0.960479 Standard E 0.269877 Observatio 140 ANOVA Regressior Residual Total df SS MS 5 246.4013 49.28026 134 9.759693 0.072834 139 256.161 Coefficientandard Err 1 Stat Intercept 61.55708 1.507019 P-value Lower 95%J 40.8469 1.69E-77 58.57645 X Variable -0.00628 0.004286 -1.46522 0.145203 -0.01476 C X Variable -0.01207 0.00581 -2.07702 0.039709 -0.02356 - X Variable -0.218 0.008022 -27.1751 2.28E-56 -0.23386 - X Variable -0.00382 0.003022 -1.26538 0.207933 -0.0098 0 X Variable 0.932755 0.035 26.64984 2.08E-55 0.86353 Compute the mean and standard deviation for each variable. Sand Saves F gnificance F 676.615 3.35E-93 Scoring Average Driving Distance Driving Accuracy 70.08 6.63 Greens in Regulation 65.67 4.97 Putts per Round Mean Standard Deviation 72.91 1.36 249.71 9.55 41.31 8.57 30.30 0.72 Correlation Coefficients Using scoring average as the dependent variable, compute the sample correlation coefficients for each independent variable. Driving Distance (x₁) Driving Accuracy (x2) Greens in Regulation (x3) -0.218 Sand Saves (x4) Putts per Round (x5) -0.006 -0.012 -0.004 0.933
Transcribed Image Text:Multiple R 0.980765 R Square 0.9619 Adjusted F 0.960479 Standard E 0.269877 Observatio 140 ANOVA Regressior Residual Total df SS MS 5 246.4013 49.28026 134 9.759693 0.072834 139 256.161 Coefficientandard Err 1 Stat Intercept 61.55708 1.507019 P-value Lower 95%J 40.8469 1.69E-77 58.57645 X Variable -0.00628 0.004286 -1.46522 0.145203 -0.01476 C X Variable -0.01207 0.00581 -2.07702 0.039709 -0.02356 - X Variable -0.218 0.008022 -27.1751 2.28E-56 -0.23386 - X Variable -0.00382 0.003022 -1.26538 0.207933 -0.0098 0 X Variable 0.932755 0.035 26.64984 2.08E-55 0.86353 Compute the mean and standard deviation for each variable. Sand Saves F gnificance F 676.615 3.35E-93 Scoring Average Driving Distance Driving Accuracy 70.08 6.63 Greens in Regulation 65.67 4.97 Putts per Round Mean Standard Deviation 72.91 1.36 249.71 9.55 41.31 8.57 30.30 0.72 Correlation Coefficients Using scoring average as the dependent variable, compute the sample correlation coefficients for each independent variable. Driving Distance (x₁) Driving Accuracy (x2) Greens in Regulation (x3) -0.218 Sand Saves (x4) Putts per Round (x5) -0.006 -0.012 -0.004 0.933
Comment on the correlation coefficients. . The independent variable least correlated with the scoring average is The independent variable most highly correlated with the scoring average is ---Select--- ---Select--- Using the single independent variable that is most highly correlated with the scoring average, develop an estimated regression equation. (Let x₁ represent driving distance, x₂ represent driving accuracy, x, represent greens in regulation, x4 represent sand saves, and x5 represent putts per round. Round your coefficients to three decimal places.) ŷ= 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 x₁ represent driving distance, x₂ represent driving accuracy, x, represent greens in regulation, X4 represent sand saves, and x represent putts per round. Round your coefficients to three decimal places.) y = 61.55707609 Compute R2. (Round your answer to three decimal places.) 0.962 Comment on the meaning of R₂2. (Consider a proportion large if it is at least 0.55.) Since R is greater than 0.55, the estimated regression equation provides a good fit.
Transcribed Image Text:Comment on the correlation coefficients. . The independent variable least correlated with the scoring average is The independent variable most highly correlated with the scoring average is ---Select--- ---Select--- Using the single independent variable that is most highly correlated with the scoring average, develop an estimated regression equation. (Let x₁ represent driving distance, x₂ represent driving accuracy, x, represent greens in regulation, x4 represent sand saves, and x5 represent putts per round. Round your coefficients to three decimal places.) ŷ= 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 x₁ represent driving distance, x₂ represent driving accuracy, x, represent greens in regulation, X4 represent sand saves, and x represent putts per round. Round your coefficients to three decimal places.) y = 61.55707609 Compute R2. (Round your answer to three decimal places.) 0.962 Comment on the meaning of R₂2. (Consider a proportion large if it is at least 0.55.) Since R is greater than 0.55, the estimated regression equation provides a good fit.
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