For example, finding differences between two groups of individuals such as the differences in musical tastes of high school students versus teachers would be important if you are the owner of a new CD store adjacent to the high school. In this case, you may want to compare differences in musical preferences between high school students and teachers according to specific categories such as Rap, Classical, Country, or Rock&Roll. Finding out this information would enable you to stock the right types of CD's that carry the greatest demand.

Determining if an association exists between two sets of data is important if you are trying to make predictions about future events or behaviors. An association shows the extent to which change in one variable is associated with change in another variable. Keep in mind that this is strictly an association and not a cause and effect relationship!

For example, determining the strength of the association between the students' grade point average and the number of CD's they purchase per month would be important information as the owner of this same CD store. If a strong association existed between grade point average and CD's purchased, you would probably want to make some adjustments to your current advertising campaign. If this strong association was positive, meaning, that the higher the grade point average, the more CD's are purchased, you would most likely begin displaying posters in school and public libraries and at book fairs as well as placing ads in the school career office next to the Ivy League college catalogs.