In correlational research, variables are most often _____.

In correlational research, variables are most often continuous because this type of research typically looks for relationships between quantities that can take on a range of values. Continuous variables allow for a more nuanced analysis of relationships, as they can show gradations and trends rather than just categories or distinct groups.

Continuous variables, such as height, weight, temperature, or time, provide a rich dataset for calculating correlation coefficients that help to identify the strength and direction of relationships. This is essential in correlational studies where the goal is to examine how changes in one variable may be associated with changes in another.

While discrete variables may sometimes be analyzed, they are generally limited to specific and distinct values—such as counts, which can restrict the insights gained from correlational analysis. Nominal and ordinal variables focus more on categories and ranks, respectively, which do not lend themselves as effectively to exploring relationships in the same way that continuous variables do. Thus, the commonly accepted practice in correlational research is to utilize continuous variables for a deeper and more flexible understanding of the data.