Independent variables are the ones that are manipulated by a researcher, whereas dependent variables are those that are impacted by the manipulation of the independent variables. Extraneous variables are those variables that have an undesirable impact in an experiment. Under ideal circumstances, manipulating the independent variable will cause a change in the dependent variable. All the other variables should not be effected. This, in turn, helps establish a causal relationship. However, sometimes other factors can have an impact on the dependent variables, in addition to the independent variable (Pourhoseingholi et al., 2016). Therefore, the extraneous variables lower the credibility of the experiment results by providing an alternative explanation, which in turn can make it difficult to establish a causal relationship which is often the goal of the researchers. It becomes even more problematic if the extraneous variables change along with the dependent variable, therefore becoming confounding variables. The major ways that researchers try to restrict the impact of extraneous variables are randomizing, restricting and matching. In randomizing, the subjects involved are all exposed to the extraneous variables, therefore creating consistent groups. In restricting, the variations in the extraneous variables are eliminated to prevent changes, and in matching, the subjects are selected in a way the extraneous factors are matched and they no longer remain extraneous factors (Kahlert et al., 2017)

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