ISO Guide 35:2006 参考材料 证明用通用和统计学原理

标准编号：ISO Guide 35:2006

中文名称：参考材料 证明用通用和统计学原理

英文名称：Reference materials — General and statistical principles for certification

发布日期：2006-01

标准范围

This Guide gives statistical principles to assist in the understanding and development of valid methods toassign 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 thisGuide are usually accompanied by a certificate and called a certified reference material (CRM). This Guidewill be useful in establishing the full potential of CRMs as aids to ensure the comparability, accuracy andcompatibility 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 andstated references. CRMs play a key role in implementing the concept of traceability of measurement results inchemistry, biology and physics among other sciences dealing with materials and/or samples. Laboratories usethese CRMs as readily accessible measurement standards to establish traceability of their measurementresults to international standards. The property values carried by a CRM can be made traceable to SI units orother internationally agreed units during production. This Guide explains how methods can be developed thatwill lead to well established property values, which are made traceable to appropriate stated references. Itcovers a very wide range of materials (matrices), ranging from gas mixtures to biological materials, and a verywide 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 theproduction of an RM and the establishment of its property values, including the associated uncertainties. Theapproaches given in this Guide can be regarded as mainstream approaches for the production and valueassignment of large groups of RMs, but appropriate amendments can be needed in a particular case. Thestatistical 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 toobtain valid property values and associated uncertainties. This Guide describes in general terms the design ofprojects to produce a CRM.

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