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:
The independent t-Test: • Independent t-Test - H...
p-Value: • p-Value: clearly expla...
Effect size online calculator:
datatab.net/st...
More information about the effect size for the unpaired t-Test:
datatab.net/tu...

[@araujopsy]

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

[@araujopsy]

Fantastic! I realized that I can rename the titles of the X and Y axes, of the graphics. In addition there is a "magic button" that helps us to understand the correct interpretation of the results. Very good!

[@datatab]

Thanks!!!

[@ewald59]

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?