Scaling data for correlation test I have a dataset of variables with different types and units (some are percentages). I was wondering whether scaling data is important before doing a correlation in this case ?
I am using rcorr() from Hmisc package on R.

Scaling should not affect correlation calculations since they are scale-adjusted calculations of covariance: $$\text{cor}(X,Y)=\frac{\text{cov}(X,Y)}{\text{sd}(X)\,\text{sd}(Y)}$$
So it should make no difference whether you do the calculations before or after rescaling.
