A standardized measure of effect size that expresses the difference between two group means in terms of their pooled standard deviation. Values of 0.2, 0.5, and 0.8 are considered small, medium, and large effects respectively.
Named after Jacob Cohen who systematized effect size interpretation in his influential 1988 book 'Statistical Power Analysis for the Behavioral Sciences.' The 'd' simply denotes this as Cohen's measure of standardized mean difference, distinguishing it from other effect size measures.
Cohen's d translates statistical jargon into real-world meaning! A d of 0.8 means the average person in the treatment group scored better than 79% of the control group—now that's a result you can visualize and understand.
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