ABSTRACT
One of the primary goals of analytic methods is to understand the relationships between variables. For instance, we might be interested in how player performance and team performance are related or how the performance in a given year is related to performance in the following year. This chapter presents several different approaches for measuring the strength of the relationship between variables; these measures summarize such a relationship by a single number. One of the appeals of the correlation coefficient is its simplicity—it reduces the possibly complex relationship between two variables to a single number. But, such simplicity has some drawbacks; hence, there are some important issues to keep in mind when basing conclusions on correlations. Finally, it is important to keep in mind that the correlation coefficient is only a single number; therefore, often it does not tell the whole story regarding the relationship between the variables, even when the relationship is a linear one.
