I have performed 61 Pearson correlation analyses between Variable A (buying ice cream) and Variable B (buying yoghurt) in my dataset (n=550). Each correlation is based on a different subset of the data (e.g., separate correlations for males and females; separate correlations for different age groups).
Fortunately (or unfortunately!), for all 61 correlations, my p value is less than 0.0007431 (which is the correction of 0.05 using Sidax).
I interpret this to mean that all the findings are significant, which in my cases is that there is a relationship between Variable A (people who buy ice cream) and Variable B (people who buy yoghurt).
Question
- Is it normal to get all significant correlations when analysing the same correlation across a large number of subsets of data?
- Is it an acceptable results (i.e., "is not questionable" etc.)?
I can assure that my procedures for data collection and analysis are robust.