Going back to the basics: the correlation coefficient

Published at February 7, 2019 · 7 min read

A measure of joint variability In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data. It is often measured by the Pearson correlation coefficient: \[\rho _{X,Y} =\textrm{corr} (X,Y) = \frac {\textrm{cov}(X,Y) }{ \sigma_X \sigma_Y } = \frac{ \sum_{1 = 1}^n [(X - \mu_X)(Y - \mu_Y)] }{ \sigma_X \sigma_Y }\] Other measures of correlation can be thought of, such as the Spearman \(\rho\) rank correlation coefficient or Kendall \(\tau\) rank correlation coefficient....