Effect Size for the independent t-test

Effect size basically indicates how strong an observed effect is. The effect size for the independent t-test tells you how strong the difference between the groups is. The independent samples t-test checks whether there is a difference between two independent groups.

Content:
- What is the effect size
- What is the difference to the p-value
- How it is calculated and interpreted
- How to calculate the effect size online

Difference effect size and p-value
The p-value says nothing about the size of the effect or difference and depends very much on the sample size.

What does this mean? If there is a difference in the population, the larger the sample, the more clearly it is indicated in the p-value. If the sample is very large, very small differences in the population can also be detected. These small differences may no longer be relevant at all.

Video about:

Effect size online calculator:

More information about the effect size for the unpaired t-Test:

[mxaraujo]

I loved this class. Well organized content, clear examples, excellent exercise at the end. I will try to reproduce it right now.

[ewald]

Thank you very much for this very clear video on effect size in t-tests! In Datatab, I very frequently use the Mann-Whitney U-test. Now I wonder how to correctly interpret the measured effect size r. In this video you have a table for interpreting the value of d. Is there a comparable table for r?