What term describes the variables investigated within a correlation, such as height and weight?

What term describes the variables investigated within a correlation, such as height and weight?

• A. Predictor Variables
• B. Co-Variables
• C. Dependent Variables
• D. Confounding Variables

Answer: (B)

Two variables studied together in a correlation are co-variables. In a correlational analysis, you’re looking at how these two measures vary in relation to each other, without assigning one as the cause or predictor of the other. Height and weight are classic examples of co-variables because you’re examining whether they tend to increase or decrease together. This differs from predictor variables, which implies a directional, causal influence in regression; from dependent variables, which are outcomes measured in experiments; and from confounding variables, which are extraneous factors that might distort the relationship being studied.

Two variables studied together in a correlation are co-variables. In a correlational analysis, you’re looking at how these two measures vary in relation to each other, without assigning one as the cause or predictor of the other. Height and weight are classic examples of co-variables because you’re examining whether they tend to increase or decrease together.

This differs from predictor variables, which implies a directional, causal influence in regression; from dependent variables, which are outcomes measured in experiments; and from confounding variables, which are extraneous factors that might distort the relationship being studied.