I calculated the Spearman's rank correlation coefficient interpretation for a given 2D dataset. I then tested its significance by doing a permutation test and obtained a p-value.
I have a problem with the interpretation of the coefficient value. While I understand that a Spearman's rank coef. value should not be mistaken/be interpreted as giving information about its significance, I still do not have a simple interpretation for the coefficient value. The significance test shows us basically how likely is the coefficient to be larger that the observed one when the Null Hypothesis is respected, but says nothing about the observed value that uses as starting point. Can for instance a value of 0.60 mean that there are 60% more ranked pairs in my data set following a monotonically crescent discrete function than otherwise?