What does the independent variable affect in an experiment?

In an experiment, the independent variable is the factor that is manipulated or controlled by the researcher to observe its effects. The dependent variable is what is measured or observed in response to changes in the independent variable. Therefore, the independent variable directly impacts the dependent variable, demonstrating how alterations to one aspect of the experimental design can produce changes in another.

For example, if a researcher is testing the effect of sleep on test performance, the amount of sleep would be the independent variable, and the test scores would be the dependent variable. As the amount of sleep varies, the researcher can assess how this influences the performance results.

Control groups, extraneous variables, and confounding variables serve different purposes within an experiment. A control group typically doesn't receive the treatment or change applied to the experimental group, which helps establish a baseline for comparison. Extraneous variables are outside factors that could influence the dependent variable and need to be controlled to avoid skewing results. Confounding variables are those that can confuse the effects of the independent variable on the dependent variable, making it difficult to determine the relationship between them. Understanding these concepts helps clarify the role of the independent variable and its influence on the overall outcome of the study.