0
$\begingroup$

I am not quite familiar with the concept of correlation. The Pearson's correlation coefficient is defined as:

$\rho_{X,Y}=\mathrm{corr}(X,Y)={\mathrm{cov}(X,Y) \over \sigma_X \sigma_Y} ={E[(X-\mu_X)(Y-\mu_Y)] \over \sigma_X\sigma_Y}$

Which makes use of Mean and Standard deviation. But, is it strict to the normal distributed data ? Since Gaussian distribution is configured by mean and variance.

I currently have some which is apparently not following normal distribution. When assessing the correlation between them, is correlation appropriate here ?

$\endgroup$
  • 1
    $\begingroup$ The correlation coefficient exists whenever the relevant expectations exist. Very much not confined to the normal. $\endgroup$ – André Nicolas Jun 4 '14 at 20:14
0
$\begingroup$

The Pearson's correlation can be used only for normal distributions. If you have some non-normal distribution, you can use the Spearman's correlation, which does not require the normality assumption.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.