Describing the Relationship between Two Quantitative Variables: Correlation
In the previous chapters, we have presented a variety of ways to describe distributions of data for both quantitative and categorical measures. In this chapter, we begin our discussion dealing with quantitative variables in situations in which we have more than one measure on each case. With two measures on each case, the measures are said to be paired; such distributions are also called bivariate distributions. For example, for a set of athletes, we might have measures of height and weight. For a set of patients, we might have measures of cholesterol and blood pressure. And for a set of newspapers, we might identify measures of circulation and advertising revenue. With three or more variables, we have multivariate distributions. An example of a multivariate distribution might include measures of motivation, intelligence, and school achievement on a set of students. The possibilities abound!