# Regression model

In 2009, the New York Yankees won 103 baseball

games during the regular season. The table on the next

page lists the number of victories (W), the earnedrun-

average (ERA), and the batting average (AVG)

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.

(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 batting

average.

(c) Which of the two models is better for predicting

the number of victories?

(d) Develop a multiple regression model that includes

both ERA and batting average. How does

this compare to the previous models?

TEAM W ERA AVG

New York Yankees 103 4.26 0.283

Los Angeles Angels 97 4.45 0.285

Boston Red Sox 95 4.35 0.270

Minnesota Twins 87 4.50 0.274

Texas Rangers 87 4.38 0.260

Detroit Tigers 86 4.29 0.260

Seattle Mariners 85 3.87 0.258

Tampa Bay Rays 84 4.33 0.263

Chicago White Sox 79 4.14 0.258

Toronto Blue Jays 75 4.47 0.266

Oakland Athletics 75 4.26 0.262

Cleveland Indians 65 5.06 0.264

Kansas City Royals 65 4.83 0.259

Baltimore Orioles 64 5.15 0.268

https://brainmass.com/statistics/regression-analysis/regression-model-461806

#### Solution Summary

This solution is comprised of a detailed explanation of regression analysis. In this solution, step-by-step explanation of this complicated topic provides students with a clear perspective of standard normal distribution to find the probability.