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Suppose X is a frequency vector that follows a central multiple hyper-geometric distribution, such as arises in random sampling of an m-category attribute from a finite population without replacement. We show that the probability that X satisfies some symmetrical, but otherwise arbitrary, interval constraints in each component decreases as the sample size increases or decreases away from one-half of the population size.

生成讲解博客的中文版本

生成AI智能校验的中文版本