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Cool point and I agree.

The sample has to represent the population, that's fundamental. If the sample is so small that it can't characterise the population distribution, then you have a problem anyway. If you're measuring a events that happen 1% of the time (or 99% of the time), a sample of 100 is not nearly enough.

If you chose an appropriate non-parametric test to cover an unknown distribution with a small sample, it maybe would have zero power (impossible to give a significant result)



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