An extraneous variable becomes a confounding variable only if it does what?

An extraneous variable is any variable other than the independent variable that could potentially influence the outcome of the study. When this extraneous variable also influences the dependent variable, it becomes a confounding variable. A confounding variable is problematic because it complicates the interpretation of the results; it can create a false impression of the relationship between the independent and dependent variables.

When an extraneous variable influences the dependent variable, it can create a situation where the observed effect of the independent variable is actually due, at least in part, to the confounding variable. For example, if a study is examining the effect of a new teaching method on student performance, and socioeconomic status (an extraneous variable) also affects student performance, then socioeconomic status can confound the results if not controlled for in the research design.

In this context, the other options do not fully capture the essence of what makes an extraneous variable confounding. Simply influencing the independent variable or being causally related to it does not necessarily result in confusion regarding the effect on the outcome. Likewise, being unrelated to the dependent variable means that it does not impact the study's results at all, thus not becoming a confounding variable.