I've been reading a variety of articles 'bout p-value controversy and since the best way to understand theory is to practise it, I devised an example. Suppose, I'm a psychologist and I conducted an experiment. My study was simple - the aim was to check the level of empathy in two groups: men and women. From some theory and earlier studies, I know, that the distribution of empathy is normal in both groups and standard deviation is equal to 1. I want to test that H_0: μ_men = μ_women, against H_1: μ_men not equal μ_women.
If I want to use Neyman-Pearson approach and omit all that p-value issue, what should I literally do?
Recently, so that I can remember, what was inside, I've read those articles:
- Lew, M.J., "To P or not to P: on the evidential nature of P-values
and their place in scientic inference"
- Lehman, 1993, "The Fisher, Neyman-Pearson Theories of Testing Hypotheses"
- Hagen, R.L., "In Praise of the Null Hypothesis Statistical Test"
- Cohen, J., "The Earth is round, p>0.05"
- Hubbard, R., "The Earth is Highly Significantly Round (p<0.0001) [this is a comment on the article of Cohen]
- Schmidt, Hunter, "Are There Benefits From NHST"
- Dienes, Z., chapters 2,3 of "Understanding Psychology as a Science"
Well I'll try to calculate as @Glen_b suggests in a few days. I hope I can present my results here.