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Appropriate rather than representative sampling, based on acceptable levels of uncertainty
journal contribution
posted on 2023-06-08, 00:59 authored by M H RamseyAppropriate sampling, that includes the estimation of measurement uncertainty, is proposed in preference to representative sampling without estimation of overall measurement quality. To fulfil this purpose the uncertainty estimate must include contribution from all sources, including the primary sampling, sample preparation and chemical analysis. It must also include contributions from systematic errors, such as sampling bias, rather than from random errors alone. Case studies are used to illustrate the feasibility of this approach and to show its advantages for improved reliability of interpretation of the measurements. Measurements with a high level of uncertainty (e.g. 50%) can be shown to be fit for some specified purposes using this approach. Once reliable estimates of the uncertainty are available, then a probabilistic interpretation of results can be made. This allows financial aspects to be considered in deciding upon what constitutes an acceptable level of uncertainty. In many practical situations ¿representative¿ sampling is never fully achieved. This approach recognises this and instead, provides reliable estimates of the uncertainty around the concentration values that imperfect appropriate sampling causes.
History
Publication status
- Published
Journal
Accreditation and Quality AssuranceISSN
0949-1775Publisher
Springer VerlagExternal DOI
Issue
7Volume
7Page range
274-280Pages
7.0Department affiliated with
- Evolution, Behaviour and Environment Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-02-06Usage metrics
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