Sensitivity analysis in practice: providing an uncertainty budget when applying supplement 1 to the GUM

Abstract

Sensitivity analysis associated with the evaluation of measurement uncertainty is a very important tool for the metrologist, enabling them to provide an uncertainty budget and to gain a better understanding of the measurand and the underlying measurement process. Using the GUM uncertainty framework, the contribution of an input quantity to the variance of the output quantity is obtained through so-called ‘sensitivity coefficients’. In contrast, such coefficients are no longer computed in cases where a Monte-Carlo method is used. In such a case, supplement 1 to the GUM suggests varying the input quantities one at a time, which is not an efficient method and may provide incorrect contributions to the variance in cases where significant interactions arise. This paper proposes different methods for the elaboration of the uncertainty budget associated with a Monte Carlo method. An application to the mass calibration example described in supplement 1 to the GUM is performed with the corresponding R code for implementation. Finally, guidance is given for choosing a method, including suggestions for a future revision of supplement 1 to the GUM.