I'm kinda brand new to statistics and I'm developing classification algorythm. My method is based on simple chi-square goodness of fit. I am counting the effect size of known cases to predict the future ones.
My problem is that I don't really know how to deal with large sample sizes, neither do I know when is a sample size "too big". Did research the answer, but did not find solution.
So what is the best approach to take when you have a double possible outcome and like 2000-3000 known cases where you know the outcome? Obviously it isn't safe for NHST as large sample sizes will yield false positives (as much as I know).
Can anyone suggest some good approach to take, or maybe a good article on the topic?
Thanks for help!