Explain the meaning of the expression “correlation does not prove causation.”
What will be an ideal response?
Even when research establishes that two variables are associated and that variation in the independent variable precedes variation in the dependent variable, we cannot be sure we identified a causal relationship between the two variables. Have you heard the old adage among researchers, “Correlation does not prove causation”? It is meant to remind us that an association between two variables might be caused by something else. If we measure children’s shoe sizes and their academic knowledge, for example, we will find a positive association. However, the association results from the fact that older children tend to have larger feet as well as more academic knowledge. As it turns out, shoe size does not cause increased knowledge or vice versa. We would say that the association between shoe size and knowledge is spurious (meaning apparently but not actually valid—that is, false).
Before we conclude that variation in an independent variable causes variation in a dependent variable, we must have reason to believe that the relationship is nonspurious. Nonspuriousness is a relationship between two variables that is not due to variation in a third variable.
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Fill in the blank(s) with correct word
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