Researchers who need to explain treatment effects to laypeople can translate Cohen's effect size (standardized mean difference) to a common language effect size--a probability of a random observation from one population being larger than a random observation from the other population. This common language effect size can be extended to represent the effect size in a p-group analysis of variance design. An example is provided to demonstrate its use in evaluation research.