The control of nuisance variables via an experimental design or statistical technique is rooted in causal inference. To infer causality in a study, a researcher must be able to infer that the results are a result of the treatment and not unchecked nuisance variables. For example, in comparing different drugs to determine which one is most effective in reducing diastolic blood pressure, changes in diastolic blood pressure must be attributable to the drugs. Clearly, if one is not careful in the assignment of individuals to the different drug treatment conditions, then one could end up making the wrong causal inference because of group idiosyncrasies. To make a fair comparison of the drugs, one must have “an equal playing field.” The researcher must control those variables ...

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