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国际标准化组织标准物质指南35
作者:     来源:      点击次数:1781      更新时间:2015-03-03

ISO Guide 35:2006 Reference materials - General and statistical principles for certification(修订中)

    This Guide gives statistical principles to assist in the understanding and development of valid methods to assign values to properties of a reference material, including the evaluation of their associated uncertainty, and establish their metrological traceability. Reference materials (RMs) that undergo all steps described in this Guide are usually accompanied by a certificate and called a certified reference material (CRM). This Guide will be useful in establishing the full potential of CRMs as aids to ensure the comparability, accuracy and compatibility of measurement results on a national or international scale.  In order to be comparable across borders and over time, measurements need be traceable to appropriate and stated references. CRMs play a key role in implementing the concept of traceability of measurement results in chemistry, biology and physics among other sciences dealing with materials and/or samples. Laboratories use these CRMs as readily accessible measurement standards to establish traceability of their measurement results to international standards. The property values carried by a CRM can be made traceable to SI units or other internationally agreed units during production. This Guide explains how methods can be developed that will lead to well established property values, which are made traceable to appropriate stated references. It covers a very wide range of materials (matrices), ranging from gas mixtures to biological materials, and a very wide range of properties, ranging from chemical composition to physical and immunoassay properties.  The approaches described in this Guide are not intended to be comprehensive in every respect of the production of an RM and the establishment of its property values, including the associated uncertainties. The approaches given in this Guide can be regarded as mainstream approaches for the production and value assignment of large groups of RMs, but appropriate amendments can be needed in a particular case. The statistical methods described exemplify the outlined approaches, and assume, e.g., normally distributed data.  In particular when data are definitely not normally distributed, other statistical methods may be preferred to obtain valid property values and associated uncertainties. This Guide describes in general terms the design of projects to produce a CRM.

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