Cohen's D is a statistical measure used to determine the effect size between two groups. It quantifies the difference in means relative to the variability of the data, allowing researchers to understand how significant the difference is. A larger Cohen's D value indicates a greater effect size, meaning the groups are more distinct from each other. Typically, Cohen's D values are interpreted as small (0.2), medium (0.5), and large (0.8) effects. This measure is particularly useful in fields like psychology and medicine, where understanding the impact of interventions or treatments is crucial for evaluating outcomes.