There is a nice treatment of resampling, i.e., permutation tests, in (from my TeX format bibliography) Sidney Siegel, {\it Nonparametric Statistics for the Beh

There is a nice treatment of resampling, i.e., permutation tests, in (from my TeX format bibliography) Sidney Siegel, {\it Nonparametric Statistics for the Behavioral Sciences,\/} McGraw-Hill, New York, 1956.\ \ Right, there was already a good book on such tests over 50 years ago. Can also justify it with an independence, identically distributed assumption. But a weaker assumption of exchangeability can also work -- I published a paper with that. The broad idea of such a statistical hypothesis test is to decide on the null hypothesis, null as in no effect (if looking for an effect, then want to reject the null hypothesis of no effect) and to make assumptions to permit calculating the probability of what you observe. If that probability is way too small then reject the null hypothesis and conclude that there was an effect. Right, it's fishy.