So I’ve been doing a lot of correlation analyses lately. Right now they’re exploratory. I get some insight into what may be going on, it guides work that we’re doing, that kind of thing.

But.

What if want to know if these correlations are actually meaningful? I’m not talking cause-and-effect meaningful, just “Are they consistent enough that we could base some other work off of them?”

Fortunately, there’s a post for that.

One of the interesting studies linked to from that post by Hui Xiang Chua is this study from Schonbrodt and Perugini that finds that in most cases your n should be 250+ to have stable correlations (that is, correlations that you wouldn’t expect to change if you sampled a different 250 cases from the same population).