Define independent variable, dependent variable, control variable, and confound. In experimental research, how do these variables contribute to inferences of causality?

Question

What will be an ideal response?

Answer 1

Ans: Varies.

In experimental research, an independent variable is a variable with two or more levels that an experimenter controls and manipulates. In experimental research, the goal is to determine if changes in an independent variable cause changes in a dependent variable, which is the variable that is measured or observed. The independent variable must be experienced before the dependent variable in order to meet the criterion of temporal precedence, which is necessary for inferences of causality. A control variable is an extraneous variable that researchers have identified as a potential source of influence on the dependent variable and they therefore control its effects, typically by holding it constant (p. 24). Controlling variables supports a researcher’s ability to infer causality by reducing one or more other alternative explanations for the results. When an extraneous variable is not controlled, varies with the independent variable, and affects the dependent variable, it is said to be a confound. Confounds provide alternative explanations for a study’s results and therefore reduce a study’s validity. Confounds, therefore, reduce researchers’ ability to infer that their independent variable caused changes in the dependent variable.