I would like to calculate simple correlations. Since my sample size is quite small and data are not normally distributed I thought about Spearman’s correlations. Then I read about bootstrapping as a distribution free method and, considering my small sample size, I decided to use it with Pearson’s correlation coefficient. However, recently I’ve found bootstrapping for Spearman correlations and got confused. If bootstrapping solves the problem with the data distribution and small sample size (i.e. one can use Pearson’s method) why I should bother with bootstrapped Spearman. Where does the problem lie? What method should I use? Are there any rules? Thanks!