I downloaded some sample data from Wikipedia and tried some statistical analysis in R:

https://drive.google.com/open?id=0B9...jJGX0RoOTRpWUU (

https://drive.google.com/open?id=0B9...jVxbDljZ0FvUmc)

But I have a question. On this page:

Quick-R: Power Analysis it says "Cohen suggests that d values of 0.2, 0.5, and 0.8 represent small, medium, and large effect sizes respectively." It gives a formula for d as absolute value of difference in means by square root of common error variance. On this page:

https://onlinecourses.science.psu.edu/stat501/node/254 it says common error variance is estimated as mean square error on linear regression. However, using the root mean square approach used in this page:

https://heuristically.wordpress.com/...-in-r-and-sas/ gives effect sizes of more than 1.

Where did I go wrong? I would also appreciate having other mistakes pointed out.