I'm currently looking at non parametric cost data (highly skewed to the right), and I'm trying to compare cost data pre and post intervention.
Traditionally I've been taught that due to the non parametric nature of the data, the traditional t-test would not be feasible, as it violates the assumption of normality. A non parametric test would be recommended such as the Wilcoxon's Signed Rank test (due to the paired nature of my data).
I've also recently heard about using bootstrapping as a method to compare cost data, however most of what I have read involved bootstrapping confidence intervals.
Can anyone shed some light on which is the prefer method in comparing skewed cost data, and methodology on using bootstrapping for hypothesis testing. I'm currently using R and is reading up on the boot package.