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 (x₂) Driving Accuracy (x₂) Greens in Regulation (x3) Sand Saves (x4) Putts per Round (x5) y = -0.006 -0.012 ý= -0.218 -0.004 Comment on the correlation coefficients. ✓. The independent variable least correlated with the scoring average is ---Select--- The independent variable most highly 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, 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.) 0.933 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, x4 represent sand saves, and x represent putts per round. Round your coefficients to three decimal places.) Compute R2. (Round your answer to three decimal places.) 0.962 Comment on the meaning of R2. (Consider a proportion large if it is at least 0.55.) Since R2 is---Select-- 2is --Select-- 0.55, the estimated regression equation ---Select--- ✓a good fit.
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 (x₂) Driving Accuracy (x₂) Greens in Regulation (x3) Sand Saves (x4) Putts per Round (x5) y = -0.006 -0.012 ý= -0.218 -0.004 Comment on the correlation coefficients. ✓. The independent variable least correlated with the scoring average is ---Select--- The independent variable most highly 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, 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.) 0.933 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, x4 represent sand saves, and x represent putts per round. Round your coefficients to three decimal places.) Compute R2. (Round your answer to three decimal places.) 0.962 Comment on the meaning of R2. (Consider a proportion large if it is at least 0.55.) Since R2 is---Select-- 2is --Select-- 0.55, the estimated regression equation ---Select--- ✓a good fit.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter4: Calculating The Derivative
Section4.CR: Chapter 4 Review
Problem 88CR
Related questions
Question
Scor 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 |
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