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The Estimation of Uncertainty by the Utilization of Validation and Quality Control Data; Lead in Gasoline by AAS

机译:利用验证和质量控制数据来估计不确定性;通过AAS引领汽油

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This protocol was developed to estimate the uncertainty of measurement of a chemical analysis by utilizing in-house validation studies and quality control data. The approach was to generate an estimate of the uncertainty across the analytical concentracion range. This was to be expressed as a mathematical equation or factor that could be inserted into a Laboratory Information Management System (LIMS) and thus produce an uncertainty estimate from an entered analytical result.The aim is to identify as many sources of uncertainty as possible and account for them by appropriatte precision and trueness studies. Any additional sources of uncertainty are evaluated by other means such as calibration certificates, published dana, etc.. It is not necessary to evaluate every source of uncertainty if they are deemed insignificant, unless there are a large number of them. Uncertainty components that are less than one third of the largest component are not evaluated in detail. A preliminary estimate of the contribution of each component or combination of components to the uncertainty is made and those that are not significant eliminated . The uncertainty contributions is expressed as standard deviation, and combined according to the appropriate rules, to give a combined standard uncertainty. Coverage factor ( 2 for normal distribution) is applied to give an expanded uncertainty.
机译:开发了该方案以通过利用内部验证研究和质量控制数据来估计化学分析的不确定性。该方法是在分析浓度范围内产生对不确定性的估计。这将表示为可以插入实验室信息管理系统(LIMS)中的数学方程或因子,从而从输入的分析结果产生不确定性估计。目的是识别尽可能多的不确定性来源和账户通过适当的精确和特鲁斯研究来为他们。任何额外的不确定性来源都是通过其他方法进行评估,如校准证书,公布的Dana等。如果他们被认为是微不足道的,则没有必要评估每个不确定的来源。除非有很多人。不详细评估低于最大组件的三分之一的不确定性组件。制造了每个组分或组分组合对不确定性的贡献的初步估计,并且没有显着消除的组件。不确定性贡献表示为标准差,并根据适当的规则组合,以提供合并的标准不确定性。覆盖因子(2正常分布)被应用于扩展不确定性。

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