If all laymen knew that n is irrelevant, it's the effect size that matters, we would be in a world of good. If the difference between means is large compared t

If all laymen knew that n is irrelevant, it's the effect size that matters, we would be in a world of good. If the difference between means is large compared to the standard deviation of the population under study, you need less n. Another fun fact: All groups are different given large enough n. Edit: I'm not endorsing the study - just pointing out that n should not be the most critical thing you look for when evaluating a study. The study is fine as a simple quasi-experiment, testing the hypothesis by induction. I don't see anyone claiming causal links here. Now a study testing the hypothesis deductively needs to be designed.