RUNNING HEAD: REGRESSION PAPER
Regression Paper
Research and Evaluation II / RES 342
July 11, 2008
Regression Paper
Introduction
The Major League Baseball (MLB) organization is a group of baseball teams that have made it to the Major League. The Major League Baseball data set provides the 2005 salaries of multiple Major League Baseball (MLB) teams as well as individual salaries of players within 30 teams (Lind, Marchal & Wathen, 2008). The MLB data set gives information such as batting averages, wins, salaries, home runs, errors, etc (Lind, Marchal & Wathen, 2008). Two specific teams stand out of the information when looking at their stats; St. Louis and Kansas City. These two teams are drastically different; one has the most wins out of the MLB data set, and the other has the least wins. With St. Louis and Kansas City both being in the major league, they are to be considered good, which makes us wonder if salaries play a part of one team doing better than another. We will look at the team scores as well as individual scores within the two teams to research if salaries affect the quality of performance. In this paper we will conduct a regression test of whether salaries affect the performances of St. Louis and Kansas City.
Hypothesis Statement
There are many differences in the two samples from the data set; we begin with the National and American league. In our data set the salary affects the performance of players based on the wins and losses. How does the salary affect the teams’ batting average? How does the salary affect the teams ERA? Kansas City has a salary of 36.9 million and their batting average is 0.263 and the ERA is 5.49. St. Louis has a salary of 92.1 million and their batting average is 0.270 and the ERA is 3. ...