Reference no: EM131688503

TEAM Baltimore Orioles Boston Red Sox Chicago White Sox 85 4.02 748 0.255 0.318 Cleveland Indians Detroit Tigers Kansas City Royals 72 4.30 676 0.265 0.317 Los Angeles Angels 89 4.02 767 0.274 0.332 Minnesota Twins New York Yankees 95 3.85 804 0.265 0.337 Oakland Athletics Seattle Mariners Tampa Bay Rays 90 319 697 0.240 0.317 Texas Rangers Toronto Blue Jays 73 4.64 716 0.245 0.309 W ERA R AVG OBP 93 3.90 712 0.247 0.311 69 4.70 734 0.260 0.315 68 4.78 667 0.25 0.324 88 3.75 726 0.268 0.335 66 4.77 701 0.260 0.325 94 3.48 713 0.238 0.310 75 3.76 619 0.234 0.296 93 3.99 808 0.273 0.334 The number of victories (W), earned run average (ERA), runs scored (R), batting average (AVG), and on- base percentage (OBP) for each team in the American League in the 2012 season are provided in the following table. The ERA is one measure of the effectiveness of the pitching staff, and a lower number is better. The other statistics are measures of effectiveness of the hitters, and higher numbers are better for each of these. (a) Develop a regression model that could be used to predict the number of victories based on the ERA. (b) Develop a regression model that could be used to predict the number of victories based on the runs scored. (c) Develop a regression model that could be used to predict the number of victories based on the batting average. (d) Develop a regression model that could be used to predict the number of victories based on the on-base percentage. (e) Which of the four models is better for predicting the number of victories? (f) Find the best multiple regression model to predict the number of wins. Use any combination of the variables to find the bestmodel.