CE  Vol.6 No.14 , August 2015
Using Baseball Data as a Gentle Introduction to Teaching Linear Regression
This effort describes a successful classroom exercise to introduce simple and multiple linear regression to working professional MBA students. The exercise starts by exploring the relationship between a baseball team’s payroll with its winning percentage. The exercise then continues with the introduction of additional predictor variables so that the students are able to build a strong predictive model for winning percentage. Student feedback consistently praises the exercise as an effective way to learn about linear regression.

Cite this paper
McMullen, P. (2015) Using Baseball Data as a Gentle Introduction to Teaching Linear Regression. Creative Education, 6, 1477-1483. doi: 10.4236/ce.2015.614148.
[1]   Albright, S. C., Winston, W. L., & Zappe, C. J. (2011) Data Analysis and Decision Making (4th ed.). Mason, Ohio: Southwestern/ Cengage Learning.

[2]   Hoaglin, D., & Velleman, P (1995). A Critical Look at Some Analyses of Major League and Baseball Salaries. The American Statistician, 49, 277-285.

[3]   USA Today.

[4]   Lewis, M. (2003). Moneyball: The Art of Winning an Unfair Game. New York: W. W. Norton & Company.

[5]   Watnik, M. R. (1988). Pay for Play: Are Baseball Salaries Based on Performance? Journal of Statistics Education, 6.