Meaningful expression of uncertainty in measurement

Author:

Cox MauriceORCID,O’Hagan Anthony

Abstract

AbstractThe Guide to the expression of uncertainty in measurement (GUM) has been the enduring guide on measurement uncertainty for metrologists since its first publication in 1993. According to the GUM, a measurement should always be accompanied by a reasoned and defensible expression of uncertainty, and the primary such expression is the standard uncertainty. In this article, we distinguish between the use of an expression of uncertainty as information for the recipient of a measurement result and its use when propagating uncertainty about inputs to a measurement model in order to derive the uncertainty in a measurand. We propose a new measure of uncertainty, the characteristic uncertainty, and argue that it is more fit for these purposes than standard uncertainty. For the purpose of reporting a measurement result, we demonstrate that standard uncertainty does not have a meaningful interpretation for the recipient of a measurement result and can be infinite. These deficiencies are resolved by the characteristic uncertainty, which we therefore recommend for use in reporting. For similar reasons, we advocate the use of the median estimate as the measured value. For the purpose of propagating uncertainty in a measurement model, we propose simple propagation of the median and characteristic uncertainty and show through some examples that this characteristic uncertainty framework is simpler and at least as reliable and accurate as the propagation of estimate, standard uncertainty and effective degrees of freedom according to the GUM uncertainty framework.

Funder

Department for Business, Energy and Industrial Strategy

Publisher

Springer Science and Business Media LLC

Subject

Safety, Risk, Reliability and Quality,Instrumentation,General Chemical Engineering,General Chemistry

Reference24 articles.

1. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP, OIML (2008) Evaluation of measurement data—Guide to the expression of uncertainty in measurement. Joint Committee for Guides in Metrology, JCGM 100

2. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP, OIML (2008) Evaluation of measurement data — Supplement 1 to the Guide to the expression of uncertainty in measurement—Propagation of distributions using a Monte Carlo method. Joint Committee for Guides in Metrology, JCGM 101:2008

3. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP, OIML (2011)Evaluation of measurement data—Supplement 2 to the Guide to the expression of uncertainty in measurement—models with any number of output quantities. Joint Committee for Guides in Metrology, JCGM 102

4. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP, OIML (2012) International Vocabulary of Metrology—Basic and General Concepts and Associated Terms. Joint Committee for Guides in Metrology, JCGM 200

5. Cox M, Shirono K (2017) Informative Bayesian Type A uncertainty evaluation, especially applicable to a small number of observations. Metrologia 54(5):642–652

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3