What is effect size and why is it important?

What is effect size and why is it important?

Effect size is a quantitative measure of the magnitude of a phenomenon. It's important because it helps to understand the practical significance of research findings.

Can you give me an example of how to calculate effect size?

Sure! One common way to calculate effect size is using Cohen's d, which is the difference between two means divided by the pooled standard deviation.

What are the different types of effect size?

There are several types of effect size, including Cohen's d, Pearson's r, and odds ratios, each suited for different types of data.

How do I interpret the value of effect size?

Generally, a small effect size is around 0.2, medium is 0.5, and large is 0.8 or above. This helps in understanding the strength of the relationship.

Why is effect size more informative than p-values?

Effect size provides information about the magnitude of an effect, while p-values only indicate whether an effect exists, not its size.