Effect size isn't conflated with the sample size (i.e., a big enough sample will show statistical significance even if the difference in groups is nominal [small effect], because if the sample is big enough you know the difference is real in the population, even if not meaningful)...so effect size gives us practical significance or the magnitude of the effect of treatment...with cohens d, an effect size of 1 means one full standard deviation difference between the control and experimental group, which is extremely large the mean of the experimental group is a full SD outside of the mean of the control group....