In this note, we discuss the use of Cohen’s D for planning difference-of-mean experiments.
Estimating sample size
Let’s imagine you are testing a new weight loss program and comparing it so some existing weight loss regimen. You want to run an experiment to determine if the new program is more effective than the old one. You’ll put a control group on the old plan, and a treatment group on the new plan, and after three months, you’ll measure how much weight the subjects lost, and see which plan does better on average.
The question is: how many subjects do you need to run a good experiment? Continue reading Cohen’s D for Experimental Planning