Increasingly, measurement uncertainty has been used by pure and applied analytical chemistry to ensure decision-making in commercial transactions and technical-scientific applications. Until recently, it was considered that measurement uncertainty boiled down to analytical uncertainty; however, over the last two decades, uncertainty arising from sampling has also been considered. However, the second version of the EURACHEM guide, published in 2019, assumes that the frequency distribution is approximately normal or can be normalized through logarithmic transformations, without treating data that deviate from the normality. Here, six examples (four from Eurachem guide) were treated by classical ANOVA and submitted to an innovative nonparametric approach for estimating the uncertainty contribution arising from sampling. Based on bootstrapping method, confidence intervals were used to guarantee metrological compatibility between the uncertainty ratios arising from the results of the traditional parametric tests and the unprecedented proposed nonparametric methodology. The present study proposed an innovative methodology for covering this gap in the literature based on nonparametric statistics (NONPANOVA) using the median absolute deviation concepts. Supplementary material based on Excel spreadsheets was developed, assisting users in the statistical treatment of their real examples.

中文翻译：

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抽样引起的测量不确定度的非参数估计

纯粹和应用分析化学越来越多地使用测量不确定度来确保商业交易和技术科学应用中的决策。直到最近，人们还认为测量不确定性可以归结为分析不确定性。然而，在过去的二十年里，抽样产生的不确定性也得到了考虑。然而，2019 年发布的 EURACHEM 指南第二版假设频率分布近似正态或可以通过对数变换进行归一化，而不处理偏离正态性的数据。在这里，六个示例（四个来自 Eurachem 指南）经过经典方差分析处理，并提交给创新的非参数方法来估计采样产生的不确定性贡献。基于自举法，置信区间用于保证传统参数测试结果和前所未有的非参数方法所产生的不确定性比率之间的计量兼容性。本研究提出了一种创新方法来弥补文献中的这一空白，该方法基于非参数统计（NONPANOVA），使用中值绝对偏差概念。开发了基于 Excel 电子表格的补充材料，帮助用户对其真实示例进行统计处理。