I'm looking into comparing charge/cost (economics) data among paired samples (i.e pre vs post). The sample size is about ~150 paired samples, where charge/cost is highly skewed with a long tail.
I'm concerned about using a paired t-test as it violates the assumption of normality, and I've been looking into using the coin package in r for its implementation of the fisher-pitman permutation test. Upon doing some research, I've also read about possibly doing a bootstrapped hypothesis test? Would a wilcoxon signed rank test be appropriate in this case? What would be most appropriate in this situation?