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Evaluation of measurement uncertainty based on the propagation of distributions using Monte Carlo simulation.

Cox, M G; Harris, P M; Siebert, B R L* (2003) Evaluation of measurement uncertainty based on the propagation of distributions using Monte Carlo simulation. Meas. Tech., 46 (9). pp. 824-833.

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Abstract

The uncertainty associated with a value of some quantity is widely recognized throughout scientific disciplines as a quantitative measure of the reliability of that value. In addition, measurement uncertainty is increasingly seen as essential in quality assurance for industry. The Guide to the Expression of Uncertainty in Measurement (GUM) provides internationally agreed recommendations for the evaluation of uncertainties. This paper outlines the current situation of uncertainty evaluation in the context of international norms and arrangements. It describes the basic ideas and concepts that underlie the GUM and serves as a brief tutorial on methods for evaluating measurement uncertainty in a manner consistent with the GUM. It recommends an approach to evaluating measurement uncertainty based on the propagation of distributions using Monte Carlo simulation. An example is presented to illustrate Monte Carlo simulation.

Item Type: Article
Keywords: uncertainty evaluation, propagation of distributions, Monte Carlo simulation
Subjects: Mathematics and Scientific Computing
Mathematics and Scientific Computing > Measurement Uncertainties
Last Modified: 02 Feb 2018 13:16
URI: http://eprintspublications.npl.co.uk/id/eprint/4316

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