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Frequency Distribution - Quantitative Salary -mil lower upper 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 < < < <...

Using the Major League Baseball Data Set available through the “Data Sets” link in the Materials section, answer the research question of whether the number of wins of a team can be explained linearly by the size of stadium, ERA, and stolen bases. Prepare a 750-1,050-word paper
describing the use of the multiple regression process to answer this research question. Be sure to include, in an appendix, your raw data table and the results of your computations in your paper, using both graphical and tabular methods of displaying data and results. THis is a team assignment, I only need to do the ERA part. Thanks for any help
Frequency Distribution - Quantitative Salary -mil cumulative lower upper midpoint width frequency percent frequency percent 20 < 30 25 10 1 3.4 1 3.4 30 < 40 35 10 3 10.3 4 13.8 40 < 50 45 10 3 10.3 7 24.1 50 < 60 55 10 3 10.3 10 34.5 60 < 70 65 10 5 17.2 15 51.7 70 < 80 75 10 3 10.3 18 62.1 80 < 90 85 10 4 13.8 22 75.9 90 < 100 95 10 4 13.8 26 89.7 100 < 110 105 10 1 3.4 27 93.1 110 < 120 115 10 0 0.0 27 93.1 120 < 130 125 10 1 3.4 28 96.6 130 < 140 135 10 0 0.0 28 96.6 140 < 150 145 10 0 0.0 28 96.6 150 < 160 155 10 0 0.0 28 96.6 160 < 170 165 10 0 0.0 28 96.6 170 < 180 175 10 0 0.0 28 96.6 180 < 190 185 10 0 0.0 28 96.6 190 < 200 195 10 0 0.0 28 96.6 200 < 210 205 10 1 3.4 29 100.0 29 100.0 Frequency Distribution - Quantitative Size cumulative lower upper midpoint width frequency percent frequency percent ### < 35,000 32,500 5,000 1 3.4 1 3.4 ### < 40,000 37,500 5,000 2 6.9 3 10.3 ### < 45,000 42,500 5,000 11 37.9 14 48.3 ### < 50,000 47,500 5,000 6 20.7 20 69.0 ### < 55,000 52,500 5,000 5 17.2 25 86.2 ### < 60,000 57,500 5,000 4 13.8 29 100.0 29 100.0 Frequency Distribution - Quantitative Size cumulative lower upper midpoint width frequency percent frequency percent ### < 35,000 32,500 5,000 1 3.3 1 3.3 ### < 40,000 37,500 5,000 2 6.7 3 10.0 ### < 45,000 42,500 5,000 11 36.7 14 46.7 ### < 50,000 47,500 5,000 6 20.0 20 66.7 ### < 55,000 52,500 5,000 6 20.0 26 86.7 ### < 60,000 57,500 5,000 4 13.3 30 100.0 30 100.0 Descriptive statistics Age count 30 mean 26.53 1st quartile 7.75 median 15.50 3rd quartile 39.00 interquartile range 31.25 mode 39.00 low extremes 0 low outliers 0 high outliers 2 high extremes 0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 0 2 0 0 0 2 4 6 8 10 12 14 16 18 20 Histogram Salary -mil Percent 3 0 ,0 0 0 3 5 ,0 0 0 4 0 ,0 0 0 4 5 ,0 0 0 5 0 ,0 0 0 5 5 ,0 0 0 0 5 10 15 20 25 30 35 40 Histogram Size Percent 3 0 ,0 0 0 3 5 ,0 0 0 4 0 ,0 0 0 4 5 ,0 0 0 5 0 ,0 0 0 5 5 ,0 0 0 0 5 10 15 20 25 30 35 40 Histogram Size Percent 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 3 3.5 4 4.5 5 5.5 6 f(x) = -0.0375x + 7.3221666667 R² = 0.5148092636 Wins ERA
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X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 Team League Built Size Surface Salary Salary -mil Wins Attendance Batting ERA HR Error SB Year Average Boston 1 1912 33871 0 123505125.0 123.5 95.0 2,847,798 0.281 4.74 199 109 45 1989 512,930 New York Yankees 1 1923 57746 0 208306817.0 208.3 95.0 4,090,440 0.276 4.52 229 95 84 1990 578,930 Oakland 1 1966 43662 0 55425762.0 55.4 88.0 2,108,818 0.262 3.69 155 88 31 1991 891,188 Baltimore 1 1992 48262 0 73914333.0 73.9 74.0 2,623,904 0.269 4.56 189 107 83 1992 1,084,408 Los Angles Angels 1 1966 45050 0 97725322.0 97.7 95.0 3,404,636 0.270 3.68 147 87 161 1993 1,120,254 Cleveland 1 1994 43368 0 41502500.0 41.5 93.0 2,014,220 0.271 3.61 207 106 62 1994 1,188,679 Chicago White Sox 1 1991 44321 0 75178000.0 75.2 99.0 2,342,804 0.262 3.61 200 94 137 1995 1,071,029 Toronto 1 1989 50516 1 45719500.0 45.7 80.0 2,014,995 0.265 4.06 136 95 72 1996 1,176,967 Minnesota 1 1982 48678 1 56186000.0 56.2 83.0 2,034,243 0.259 3.71 134 102 102 1997 1,383,578 Tampa Bay 1 1990 44027 1 29679067.0 29.7 67.0 1,141,915 0.274 5.39 157 124 151 1998 1,441,406 Texas 1 1994 52000 0 55849000.0 55.8 79.0 2,525,259 0.267 4.96 260 108 67 1999 1,720,050 Detroit 1 2000 40000 0 69092000.0 69.1 71.0 2,024,505 0.272 4.51 168 110 66 2000 1,988,034 Seattle 1 1999 45611 0 87754334.0 87.8 69.0 2,724,859 0.256 4.49 130 86 102 2001 2,264,403 Kansas City 1 1973 40529 0 36881000.0 36.9 56.0 1,371,181 0.263 5.49 126 125 53 2002 2,383,235 Atlanta 0 1993 50062 0 86457302.0 86.5 90.0 2,520,904 0.265 3.98 184 86 92 2003 2,555,476 Arizona 0 1998 49075 0 62329166.0 62.3 77.0 2,059,327 0.256 4.84 191 94 67 2004 2,486,609 Houston 0 2000 42000 0 76799000.0 76.8 89.0 2,805,060 0.256 3.51 161 89 115 2005 2,632,655 Cincinnati 0 2003 42,059 0 61892583.0 61.9 73.0 1,923,254 0.261 5.15 222 104 72 New York Mets 0 1964 55775 0 101305821.0 101.3 83.0 2,827,549 0.258 3.76 175 106 153 Pittsburgh 0 2001 38127 0 38133000.0 38.1 67.0 1,817,245 0.259 4.42 139 117 73 Los Angeles Dodgers 0 1962 56000 0 83039000.0 83.0 71.0 3,603,680 0.253 4.38 149 106 58 San Diego 0 2004 42,445 0 63290833.0 63.3 82.0 2,869,787 0.257 4.13 130 109 99 Washington 0 1961 56000 0 48581500.0 48.6 81.0 2,730,352 0.252 3.87 117 92 45 San Francisco 0 2000 40800 0 90199500.0 90.2 75.0 3,181,020 0.261 4.33 128 90 71 St Louis 0 1966 49625 0 92106833.0 92.1 100.0 3,542,271 0.270 3.49 170 100 83 Florida 0 1987 42531 0 60408834.0 60.4 83.0 1,852,608 0.272 4.16 128 103 96 Philadelphia 0 2004 43500 0 95522000.0 95.5 88.0 2,665,304 0.270 4.21 167 90 116 Milwaukee 0 2001 42400 0 39934833.0 39.9 81.0 2,211,323 0.259 3.97 175 119 79 Chicago Cubs 0 1914 38957 0 87032933.0 87.0 79.0 3,100,092 0.270 4.19 194 101 65 Colorado 0 1995 50381 0 48155000.0 48.2 67.0 1,914,385 0.267 5.13 150 118 65
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