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.

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TEAM Baltimore Orioles 93 3.90 712 0.247 0.311 Boston Red Sox Chicago White Sox 85 4.02 48 0.255 0318 Cleveland Indians 68 .78 667 025 0.324 Detroit Tigers Kansas City Royals 72 4.3 676 0.265 0317 Los Angeles Angels 89 402767 0.274 0332 Minnesota Twins 66 4.77 700260 0.325 New York Yankees 95 3.85 804 0265 0.337 Oakland Athletics 94 3.48 713 0238 0.310 Seattle Mariners 75 3.76 619 0.23 0.296 Tampa Bay Rays 90 3.19 697 0240 0.317 Texas Rangers Toronto Blue Jays 73 464 716 0.245 0.309 WERA R AVG OBE, 69 4.70 734 .260 0.315 8 88 3.75 726 0268 0.335 93 3,99 808 0273 0.334