# Correlation between normal distributed and non normal distributed variables

If one variable is normal distributed and the other is non normal distributed, which kind of correlation do we use?

I am not sure which correlation is right to use.

• The Pearson correlation coefficient doesn't require the variables to have a certain distribution. The only connection I see between the case you are describing and correlation is that, if the variables are uncorrelated, it does not mean they are independent (which is simply the general case). Commented Nov 12, 2013 at 22:37
• My variables are age which is normally distributed and number of activities which non normally distributed. I used Spearman rho cause it doesn't require any certain distribution. The coefficience is a negative number (-.316) does it mean anything specific as for the correlation? Commented Nov 12, 2013 at 22:55
• I think it would be better if you would either edit and amend your original question, or, since this seems to be an entirely different question, post this separately. I only answered you with a comment since I think that the fact that your distributions are different doesn't matter in the first place and you can use the most popular coefficient - Pearson, or the non-parametric - Spearman. Commented Nov 12, 2013 at 23:09
• The big distinction between Spearman and Pearson correlation isn't any distributional assumption (neither assumes any, unless perhaps you're performing a test), but between linear correlation (Pearson) and monotonic association (Spearman). If you don't think the association is linear, then Spearman may make more sense. Commented Nov 13, 2013 at 0:29