Sample sizes for confidence limits for reliability.
Author(s) -
John L. Darby
Publication year - 2010
Language(s) - English
Resource type - Reports
DOI - 10.2172/972864
Subject(s) - hypergeometric distribution , reliability (semiconductor) , sample (material) , statistics , sample size determination , reliability engineering , stockpile , confidence interval , binomial distribution , population , sampling (signal processing) , computer science , mathematics , engineering , nuclear physics , physics , telecommunications , power (physics) , thermodynamics , demography , quantum mechanics , sociology , detector
We recently performed an evaluation of the implications of a reduced stockpile of nuclear weapons for surveillance to support estimates of reliability. We found that one technique developed at Sandia National Laboratories (SNL) under-estimates the required sample size for systems-level testing. For a large population the discrepancy is not important, but for a small population it is important. We found that another technique used by SNL provides the correct required sample size. For systems-level testing of nuclear weapons, samples are selected without replacement, and the hypergeometric probability distribution applies. Both of the SNL techniques focus on samples without defects from sampling without replacement. We generalized the second SNL technique to cases with defects in the sample. We created a computer program in Mathematica to automate the calculation of confidence for reliability. We also evaluated sampling with replacement where the binomial probability distribution applies.
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