Develop a regression model that could be used to predict


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.

Team W ERA R AVG OBP
Baltimore Orioles 93 3.90 712 0.247 0.311
Boston Red Sox 69 4.70 734 0.260 0.315
Chicago White Sox 85 4.02 748 0.255 0.318
Cleveland Indians 68 4.78 667 0.251 0.324
Detroit Tigers 88 3.75 726 0.268 0.335
Kansas City Royals 72 4.30 676 0.265 0.317
Los Angeles Angels 89 4.02 767 0.274 0.332
Minessota Twins 66 4.77 701 0.260 0.325
New York Yankees 95 3.85 804 0.265 0.337
Oakland Athletics 94 3.48 713 0.238 0.310
Seattle Mariners 75 3.76 619 0.234 0.296
Tampa Bay Rays 90 3.19 697 0.240 0.317
Texas Rangers 93 3.99 808 0.273 0.334
Toronto Blue Jays 73 4.64 716 0.245 0.309


(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.

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