#### Effect Size for Independent Samples t-Test (Jump to: Lecture | Video )

Remember that effect size allows us to measure the magnitude of mean differences. This is usually calculated
after rejecting the null hypothesis in a statistical test. If the null hypothesis is not rejected, effect
size has little meaning.

Let's say we already have this data from a previous t-test:

One method of calculating effect size is cohen's d:

With cohen's d, remember that:

d = 0.2, small effect

d = 0.5, medium effect

d = 0.8, large effect

So, our d of 3.14 would be a very large effect size.

Another method of calculating effect size is with r squared:

With r squared:

0.718 indicates a very large effect. Our means are likely very different.