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Software Support for Metrology Best Practice Guide No. 6. Uncertainty evaluation.

Cox, M G; Harris, P M (2010) Software Support for Metrology Best Practice Guide No. 6. Uncertainty evaluation. NPL Report. MS 6

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This guide provides best practice in the evaluation of uncertainty within metrology, and in the support to this topic given by a treatment that is probabilistic. It is motivated by two principle considerations. The first is that although the primary guide on uncertainty evaluation, the 'Guide to the expression of uncertainty in measurement' (GUM), can be expected to be very widely applicable, the approach it predominantly endorses contains some limitations. The other is that on the basis of the authors' considerable contact with practitioners in the metrology community it is evident that important classes of problem are encountered that are subject to these limitations. A further consideration is that measurement models are encountered in practice that lie outside the scope of the model type (viz., a measurement function with a single (scalar) output quantity) that is the focus of the presentation given in the GUM. Central to consideration is the need to carry out uncertainty evaluation in as scientific a manner as economically possible. Although several approaches to uncertainty evaluation exist, the GUM has been very widely adopted (and is strongly supported by the authors of this guide). The emphasis of this guide is on making good use of the GUM, on aspects that yield greater generality, and especially on the provision in some cases of measurement uncertainties that are more objectively based and numerically more sustainable. The guide is also concerned with validating the current usage of the GUM in circumstances where there is doubt concerning its applicability. The relationship of this guide to the work being carried out by the Joint Committee on Guides in Metrology to prepare a new edition of the GUM and to provide supporting documents to the GUM is indicated.

Item Type: Report/Guide (NPL Report)
NPL Report No.: MS 6
Subjects: Mathematics and Scientific Computing
Mathematics and Scientific Computing > Measurement Uncertainties
Last Modified: 02 Feb 2018 13:14
URI: http://eprintspublications.npl.co.uk/id/eprint/4655

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