THe Golfing Statistics provides data for a portion of the 2010 professional seas
ID: 2948719 • Letter: T
Question
THe Golfing Statistics provides data for a portion of the 2010 professional season for the top 25 golfers.
A) Find the best multiple regression model for predicting earnings/event as a function of the remaining variables.
B) Find the best multiple regression model for predicting average score as a function of the other variables except earning sand events.
Golfing Statistics
Golfing Statistics
Earnings/Event Events Avg. Score GIR (%)* Driving Distance Driving Accuracy (%) Putts/Round $239,493.68 22 70.37 67.9 288.4 60.2 31.82 $177,249.18 28 69.43 69.4 286.9 67.9 31.30 $218,619.18 22 70.23 67.1 276.0 71.0 31.81 $186,380.08 24 70.46 68.0 308.5 56.4 31.81 $209,511.75 20 69.78 68.3 282.9 68.5 31.43 $181,987.29 21 70.34 65.1 299.1 52.7 31.72 $162,536.13 23 69.92 66.3 287.8 65.2 31.68 $174,534.95 21 70.25 65.3 277.0 62.4 31.52 $135,353.70 27 70.64 68.0 291.8 67.9 32.35 $212,540.82 17 69.93 68.7 294.2 61.3 31.55 $297,079.50 12 70.26 69.3 298.7 61.3 32.31 $168,904.45 20 69.96 66.0 291.4 64.8 31.79 $135,791.58 24 70.21 68.5 309.8 55.7 31.73 $133,695.52 23 70.53 68.2 289.1 64.8 31.86 $112,192.04 26 70.59 66.5 279.7 71.2 31.30 $215,121.67 12 70.22 66.5 292.4 60.1 32.29 $183,922.93 14 70.86 62.9 287.2 52.0 31.99 $150,251.76 17 70.94 66.2 300.0 62.6 32.31 $183,356.69 13 71.13 66.9 291.7 67.1 32.06 $130,274.35 17 71.53 62.5 286.8 62.7 32.47 $286,285.40 5 69.73 69.4 308.4 70.6 32.09 $72,708.05 19 70.79 61.9 292.1 56.7 31.50 $99,597.31 13 71.07 64.1 295.8 57.2 31.52 $85,557.56 9 71.10 64.1 290.4 69.3 31.95 $46,406.25 8 71.24 61.1 289.9 65.5 32.31 *GIR: Greens in RegulationExplanation / Answer
Here i copied all data intoExcel:
A) then go to data analysis-> Regression -> In place Input Y range input vector Earnings/Event -> In place of Input X range input all vector other than Earnings/Event-> In cell of labels tick mark. -> Also tick for residuals,standardies residuals -> Select output range -> Then press ok.
Then we get following output.
Thus the regression equation is:
Earnings/Event= (-4747.681755)*Event-(45049.73715)*Avg.score+(22416.76093)*GIR-
(3429.3112)*Driving Distance-(5413.9034)*Driving Accuracy+
(57949.81073)*Putts/Round+1437821.623
B) then go to data analysis-> Regression -> In place Input Y range input vector Avg. Score -> In place of Input X range input all vector other than Avg. Score-> In cell of labels tick mark. -> Also tick for residuals,standardies residuals -> Select output range -> Then press ok.
The regression equation :
Avg.score=(-0.015690723)*Event-(5.072*10^(-6))*Earnings/Event-(0.01239611)*GIR-
(0.012270372)*Driving Distance-(0.02112577)*Driving Accuracy+
(0.74837883)*Putts/Round+53.49098873
SUMMARY OUTPUT Regression Statistics Multiple R 0.907422179 R Square 0.82341501 Adjusted R Square 0.764553347 Standard Error 29533.55374 Observations 25 ANOVA df SS MS F Significance F Regression 6 73209748917 12201624820 13.98898648 6.49787E-06 Residual 18 15700154337 872230796.5 Total 24 88909903254 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1437821.623 1347403.762 1.067105246 0.300028237 -1392968.633 4268611.879 -1392968.633 4268611.879 Events -4747.681755 1287.532815 -3.687425828 0.001685195 -7452.687819 -2042.675692 -7452.687819 -2042.675692 Avg. Score -45049.73715 19510.79217 -2.308965047 0.033023094 -86040.39037 -4059.083927 -86040.39037 -4059.083927 GIR (%)* 22416.76093 4698.689378 4.770853981 0.000152822 12545.18087 32288.34099 12545.18087 32288.34099 Driving Distance -3429.311291 995.8982298 -3.443435472 0.002898633 -5521.615828 -1337.006753 -5521.615828 -1337.006753 Driving Accuracy (%) -5413.9034 1450.334544 -3.732865237 0.001522986 -8460.943204 -2366.863596 -8460.943204 -2366.863596 Putts/Round 57949.81073 23557.912 2.459887393 0.024242869 8456.474262 107443.1472 8456.474262 107443.1472 RESIDUAL OUTPUT Observation Predicted Earnings/Event Residuals Standard Residuals 1 214353.3044 25140.3756 0.982936408 2 195162.1174 -17912.93735 -0.700358602 3 186200.664 32418.51596 1.267496562 4 154109.3185 32270.76149 1.26171967 5 210720.1049 -1208.354893 -0.047244164 6 155801.2113 26186.07871 1.023821225 7 160886.2832 1649.846847 0.064505581 8 176021.9942 -1487.04422 -0.058140337 9 158059.8278 -22706.12781 -0.887762382 10 234355.2581 -21814.43814 -0.85289917 11 285287.2656 11792.23444 0.461051846 12 162796.8305 6107.619451 0.23879522 13 171275.7761 -35484.1961 -1.387358281 14 184136.2119 -50440.69187 -1.972126164 15 94216.33916 17975.70084 0.702812524 16 251264.6734 -36143.00345 -1.413116278 17 176537.2319 7385.698139 0.288765439 18 149926.8976 324.8624437 0.012701446 19 165663.1729 17693.5171 0.691779726 20 94403.02563 35871.32437 1.402494191 21 248276.4951 38008.90487 1.486069144 22 62891.1652 9816.884801 0.383819782 23 113843.7961 -14246.48611 -0.557007982 24 109411.4995 -23853.93946 -0.93263943 25 83751.35566 -37345.10566 -1.460115975Related Questions
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