Assume the null distribution is a centrally symmetric probability distribution, so and have the same law. A sign-flip randomization test draws signs independently and recomputes, for example,The exact p-value averages over all sign vectors:With random sign vectors, including the observed configuration, the standard Monte Carlo version is , where is the observed statistic. Joint sign invariance under the null makes this finite-sample valid.
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