## 1.7 Effect Size

The effect size is a measure to quantify the magnitude of the relationship between two variables. Effect size is typically expressed as Cohen’s d. Cohen described a small effect = 0.2, medium effect size = 0.5 and large effect size = 0.8. Given a large enough sample size, even very small effect sizes can produce significant p-values (0.05 and below). In other words, statistical significance explores the probability our results were due to chance and effect size explains the importance of our results. G*Power is a great open-source program used to quickly calculate the required sample size based on your power and effect size parameters.