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Compendium of examples: good practice in evaluating measurement uncertainty

Name: Compendium of examples: good practice in evaluating measurement uncertainty
Keywords: Measurement uncertainty, calibration, testing, GUM, conformity assessment, Bayesian inference

Research datakeyboard_double_arrow_right Dataset 20 Nov 2020 English Publisher:Zenodo

Authors: A.M.H Van Der Veen; M.G. Cox; J. Greenwood; A. Bo��njakovic; V. Karahod��ic; S. Martens; K. Klauenberg; +60 Authors

doi: 10.5281/zenodo.5142180 , 10.5281/zenodo.4282088

Compendium of examples: good practice in evaluating measurement uncertainty

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Abstract

This document illustrates good practice in the evaluation of measurement uncertainty. It contains examples from a variety of areas in calibration and testing, and illustrates the use of the methods from the ��Guide to the expression of Uncertainty in Measurement�� and its supplements, as well as Bayesian approaches. Compendium_M36.pdf: document

Related Organizations

LGC
United Kingdom

Keywords

Measurement uncertainty, calibration, testing, GUM, conformity assessment, Bayesian inference

2 Research products, page 1 of 1

Good practice in evaluating measurement uncertainty
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Compendium of examples: good practice in evaluating measurement uncertainty
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Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average