It is well known that sample moments are more sensitive and less robust than order statistics for robustness with respect to outliers. In this article, we show that the situation is exactly the opposite for robustness with respect to rounding. For large and very large sample sizes, statistical procedures based on order statistics become non-applicable even for very mild data rounding while procedures based on sample moments work perfectly for this rounding level. The comparison of sample moments and order statistics is made for tests for normality and tests for exponentiality.

中文翻译：

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关于样本量大时四舍五入对假设检验的影响

众所周知，对于异常值的鲁棒性，样本矩比阶数统计更敏感，但鲁棒性较差。在本文中，我们展示了在舍入方面的稳健性情况正好相反。对于大样本量和非常大的样本量，即使对于非常温和的数据舍入，基于订单统计的统计程序也变得不适用，而基于样本矩的程序非常适合这种舍入级别。样本矩和阶数统计的比较用于正态性检验和指数性检验。