Validating the applicability of the GUM procedure

This paper is directed at practitioners seeking a degree of assurance in the quality of the results of an uncertainty evaluation when using the procedure in the Guide to the Expression of Uncertainty in Measurement (GUM) (JCGM 100 : 2008). Such assurance is required in adhering to general standards such as International Standard ISO/IEC 17025 or other sector-specific standards. We investigate the extent to which such assurance can be given. For many practical cases, a measurement result incorporating an evaluated uncertainty that is correct to one significant decimal digit would be acceptable. Any quantification of the numerical precision of an uncertainty statement is naturally relative to the adequacy of the measurement model and the knowledge used of the quantities in that model. For general univariate and multivariate measurement models, we emphasize the use of a Monte Carlo method, as recommended in GUM Supplements 1 and 2. One use of this method is as a benchmark in terms of which measurement results provided by the GUM can be assessed in any particular instance. We mainly consider measurement models that are linear in the input quantities, or have been linearized and the linearization process is deemed to be adequate. When the probability distributions for those quantities are independent, we indicate the use of other approaches such as convolution methods based on the fast Fourier transform and, particularly, Chebyshev polynomials as benchmarks.