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Lot Acceptance and Compliance Testing Using the Sample Mean and an Extremum

机译:使用样本均值和极值进行批次验收和一致性测试

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摘要

In industry, one sometimes compares a sample mean and minimum, or a mean and maximum, to reference values to determine whether a lot should be accepted. Particularly prominent examples of such procedures are "Category B" sampling plans for checking the net contents of packaged goods. Because the exact joint distribution of an Extremum and the mean of a sample is usually complicated, establishing these reference values using statistical considerations typically involves crude approximations or simulation, even under the assumption of normality. The purpose of this article is to use the Saddlepoint method to develop a fairly simple and very accurate approximation to the joint cumulative distribution function (cdf) of the mean and an Extremum of a normal sample. This approximation can be used to establish statistically based acceptance criteria or to evaluate the performance of sampling plans based on criteria derived in other ways. These uses are illustrated with examples.
机译:在行业中,有时会将样本均值和最小值或均值和最大值与参考值进行比较,以确定是否应接受大量样品。这种程序的特别突出的例子是用于检查包装货物净含量的“ B类”抽样计划。由于极值和样本均值的精确联合分布通常很复杂,因此即使考虑到正态性,使用统计考虑确定这些参考值也通常涉及粗略的近似或模拟。本文的目的是使用Saddlepoint方法开发一种非常简单且非常准确的近似值,以近似均值和极值的联合累积分布函数(cdf)。该近似值可用于建立基于统计的接受标准,或基于以其他方式得出的标准来评估抽样计划的绩效。通过示例说明了这些用法。

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