ABSTRACT
In this chapter we examine the association between two variables, an independent variable and a dependent variable, but in this case, both variables are continuous or at least have many ordered levels and, thus, may be approximately continuous. Many methodologists choose to describe a correlation, such as that resulting from a Pearson product-moment correlation, as a relation between two variables without designating one as the independent variable and one as the dependent variable. Others choose to describe the relation as occurring between two dependent variables. Our emphasis on designating one variable as the independent variable and the other variable as the dependent variable follows from the previous chapters on design and the natural lead into linear regression. We discuss the Pearson product-moment correlation, (r), the nonparametric equivalent, Spearman rank-order correlation (rs), and also introduce linear regression. In our previous discussion of statistical analyses in chapters 14 and 15, the independent variable has been categorical, and typically not more than three or four categories. The analyses that we discussed conformed to the research approaches of randomized experimental, quasi-experimental, and comparative. Now we would like you to consider an independent variable that is continuous. A continuous independent variable is almost always an attribute independent variable. Therefore, when the independent variable and the dependent variable are continuous, the research approach is associational.
