For large uncertainties, calculating the expanded uncertainty using a normal distribution for the values of the measurand can lead to negative values for the lower limit of the expanded uncertainty and unrealistic large values for the upper limit, when the relative uncertainty is constant over wide concentration range. Using the lognormal distribution overcomes these problems and is particularly important when the relative uncertainty is larger than 10%; below this value, both distributions give almost identical results. The use of the lognormal distribution can be appropriate when the model equation for the derivation of the value of the measurand consists of products of input quantities, with positive values. Most measurement results are given as a mean and a relative uncertainty, and the purpose of this paper is to show how, for a lognormal distribution, the expanded uncertainty can be derived directly from these two parameters.

中文翻译：

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使用对数正态分布计算大不确定性的扩展不确定性

对于较大的不确定度，当相对不确定度在较宽的浓度范围内保持恒定时，使用被测量值的正态分布计算扩展不确定度会导致扩展不确定度的下限为负值，上限为不切实际的大值. 使用对数正态分布克服了这些问题，当相对不确定性大于 10% 时尤为重要；低于此值，两种分布给出几乎相同的结果。当用于推导被测量值的模型方程由输入量的乘积和正值组成时，使用对数正态分布可能是合适的。大多数测量结果以平均值和相对不确定度的形式给出，本文的目的是展示如何，