Develop a regression model

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In 2009, the New York Yankees won 103 baseball games during the regular season. The table below lists the number of victories (W), the earned run-average (ERA), and the batting average (BA) of each team in the American League. The ERA is one measure of the effectiveness of the pitching staff, and a lower number is better. The batting average is one measure of effectiveness of the hitters, and a higher number is better. 

Team

W

ERA

BA

Yankees

103

4.26

0.283

Angels

97

4.45

0.285

Red Sox

95

4.35

0.270

Twins

87

4.5

0.274

Rangers

87

4.38

0.260

Tiger

86

4.29

0.260

Marines

85

3.87

0.258

Rays

84

4.33

0.263

White Sox

79

4.14

0.258

Blue jay

75

4.47

0.266

Athletics

75

4.26

0.262

Indians

65

5.06

0.264

Royal

65

4.83

0.259

Orioles

64

5.15

0.268

  1. Develop a regression model that could be used to predict the number of victories based on the ERA. 
  2. Develop a regression model that could be used to predict the number of victories based on the BA.
  3. Calculate the values of r for both models and interpret the value of r in the context of this problem
  4. Which of the two models is better for predicting the number of victories?
  5. Should both variables be included in the model? Why or why not?

Reference no: EM133066439

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