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Correlation is a measure of the degree or strength of relationship between two or more variables. It does not prove causation because we may not know which variable came first or whether alternative explanations for the presumed effect exist. For example, earnings and schooling are correlated, but it is unknown which one goes first. Correlations also do little to rule out alternative explanations for a relationship between two variables such as education and income. That relationship may not be causal at all but rather due to a confounding variable, such as family socioeconomic status, that causes both earning and schooling.

Marco A. Muñoz
10.4135/9781412950558.n115
Further Reading
Shadish, W. R., Cook, T. D., & Campbell, D. T.(2002)Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.
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