Student

Descriptive Statistics Paper

Team C

University of Phoenix

May XX, 20XX

Descriptive Statistics

Descriptive statistics, or numerical summaries, are used to characterize data to gain a clearer understanding of the population sample. Within a 162 game schedule, one would think that winning 50 percent of the time would be an easy feat for most, if not all teams; however after analyzing the 2005 MLB data set, one can conclude that winning more than half the games in a season is difficult for most teams.

During the 2005 season, individual team wins ranged from 56 total wins, on the low end, to 100 total wins for the best team in 2005. Examining data beyond total wins and losses, these authors introduced individual team salaries, attempting to show a cause-and-effect relationship between salary and performance. The 2005 MLB data set showed a range of team salaries from 29.7 million to 208.3 million, which in contrast to wins, lead to the development of this business question: do team salaries translate into wins or losses?

Dispersion, Central Tendency and Skew

The mean and median of each data category were relatively similar in comparison. The mean of all combined MLB team salaries for the 2005 season was 73.1 million dollars, while the median was 66.2 million dollars. Regarding combined team wins for the 2005 season, the mean 81.0, while median was also 81.0.

Standard deviation provided some detail into how close the 29 different teams were to the mean of salaries and wins. The deviation for salaries was far higher than that of wins, which can lead one to conclude that there are many teams overpaying their players, yet not realizing performance results; on the contrary, there are many other teams that are limiting their wins by keeping team salaries low. Descriptive statistics offered a glance into the relationship among the variables in the data; however, more details must be scrutinized in order to draw a firm conclusion....