Your input and results
This uses parametric assumptions, i.e. that distributions of the variables in the population are Gaussian. That's always dodgy! If distributions are not Gaussian the CI can have coverage considerably off from what you want but if all you have is the observed correlations and the n it's as good as you can get. If you have the raw data I recommend you use the bootstrap CI of the Pearson correlation. I'll put up an app to do that when I can.
App created by Chris Evans PSYCTC.org 27.xi.23 and last updated (adding SE calculations) 18.xi.24. It is licenced under a Creative Commons, Attribution Licence-ShareAlike Please respect that and put an acknowledgement and link back to here if re-using anything from here.
Background and related resources
This shiny app is one of a growing number in, my shiny serverThey complement:
- my Rblog of posts about using R
- the glossary linked with
- the OMbook
- the CECPfuns R package
- and it's all part of the resources of PSYCTC.org
- and linked with the CORE system web site
There is a form if you want to contact me: so do please use that if you think there is anything wrong here or anything that could be improved.
There is also now an Email announcement list, never updating more than monthly, where I will put up developments of new apps here, a summary of updates to the glossary and new posts in the Rblog. You can sign up for that here.