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Homepage>ISO Standards>ISO 21748:2017-Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty evaluation-General information
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download between 0-24 hoursReleased: 2017
ISO 21748:2017-Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty evaluation-General information

ISO 21748:2017

ISO 21748:2017-Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty evaluation-General information

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Standard´s number:ISO 21748:2017
Pages:38
Edition:2
Released:2017
DESCRIPTION

ISO 21748:2017


ISO 21748:2017 gives guidance for - evaluation of measurement uncertainties using data obtained from studies conducted in accordance with ISO 5725‑2, and - comparison of collaborative study results with measurement uncertainty (MU) obtained using formal principles of uncertainty propagation (see Clause 14). ISO 5725‑3 provides additional models for studies of intermediate precision. However, while the same general approach may be applied to the use of such extended models, uncertainty evaluation using these models is not incorporated in this document. ISO 21748:2017 is applicable to all measurement and test fields where an uncertainty associated with a result has to be determined. ISO 21748:2017 does not describe the application of repeatability data in the absence of reproducibility data. ISO 21748:2017 assumes that recognized, non-negligible systematic effects are corrected, either by applying a numerical correction as part of the method of measurement, or by investigation and removal of the cause of the effect. The recommendations in this document are primarily for guidance. It is recognized that while the recommendations presented do form a valid approach to the evaluation of uncertainty for many purposes, it is also possible to adopt other suitable approaches. In general, references to measurement results, methods and processes in this document are normally understood to apply also to testing results, methods and processes.