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There is now a self-consistent and almost complete body of concepts and practices relating to the quality of analytical data. The need for quality in sampling is also well recognized but there has been no comparable development of an over-all approach or, in some aspects, even of a basic methodology. This paper discusses the prospects for a complete approach to quality in sampling. It shows that virtually all of the concepts and practices used in analysis can be adapted, with only a slight change of detail, for application to sampling. Topics considered include the sampling analogues of trueness, bias, accuracy error, precision, uncertainty, traceability, fitness for purpose, reference materials, collaborative trials, proficiency tests and internal quality control.
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