Cohen’s effect size classes have two selling points. First, they are easy to grasp. You just compare your numbers with his thresholds to get a ready-made interpretation of your result. Second, although they are arbitrary, they are sufficiently grounded in logic for Cohen to hope that his cut-offs “will be found to be reasonable by reasonable people" (1988: 13). In deciding the boundaries for the three size classes, Cohen began by defining a medium effect as one that is “visible to the naked eye of the careful observer" (Cohen 1992: 156). To use his example, a medium effect is equivalent to the difference in height between fourteen- and eighteen-year-old girls, which is about one inch. He then defined a small effect as one that is less than a medium effect, but greater than a trivial effect. Small effects are equivalent to the height difference between fifteen- and sixteen-year-old girls, which is about half an inch. Finally, a large effect was defined as one that was as far above a medium effect as a small one was below it. In this case, a large effect is equivalent to the height difference between thirteen- and eighteen-year-old girls, which is just over an inch and a half.

Effect sizes seen in the social sciences are oftentimes very small (Rosnow & Rosenthal, 2003). This has led to difficulties in their interpretation. There is no agreement on what magnitude of effect is necessary to establish practical significance. Cohen (1992) of fers the value of r .1, as a cut-off for “small” effects (which would indicate only a 1% overlap in variance between two variables). However, Cohen did not anchor his recommendations across effect sizes; as such, his recommendations for r and d ultimately differ in magnitude when translated from one to another. For instance, Cohen suggests that r
.3 and d
.5 each indicate a cut-off for moderate effects, yet r
.3 is not the equivalent of d
.5. Other scholars suggest a minimum of r
.2 (Franzblau, 1958; Lipsey, 1998) or .3 (Hinkle, Weirsma, & Jurs, 1988). In the current article, all effect size recommendations, where possible, are anchored to a minimum of r
.2, for practical significance (Franzblau, 1958; Lipsey, 1998). These readily convert from r to d for instance, without altering the interpretation. Note that this is a suggested minimum not a guarantee that observed effect sizes larger than r
.2 are practically significant. Such cut-offs are merely guidelines, and should not be applied rigidly (Cohen, 1992; Snyder & Lawson, 1993; Thompson, 2002).