What is the term used to describe variables that may affect the dependent variable but are not controlled for?

The term that describes variables which may impact the dependent variable but are not adequately controlled for is known as confounding variables. These variables can create misleading associations between the independent and dependent variables, making it difficult to determine whether the changes observed in the dependent variable are truly due to the manipulation of the independent variable or influenced by other factors.

When confounding variables are present, they can introduce bias into the results of an experiment, leading researchers to draw incorrect conclusions about the relationships between variables. Recognizing and controlling for confounding variables is crucial in research design to ensure that the outcomes reflect direct effects rather than spurious correlations created by other underlying factors.

In contrast, demand characteristics refer to cues that might influence participants to behave in a certain way during the experiment, potentially skewing results. Extraneous variables are any variables other than the independent variable that could affect the dependent variable, but they differ from confounding variables in that they do not systematically bias the results unless they correlate with the independent variable. Independent variables are those that researchers manipulate in order to observe effects on the dependent variable.