Examples in major areas demonstrating choice of method

The aim of this work package is to develop worked examples of uncertainty evaluations in major areas in industry, trade, science and regulation. The examples illustrate the practical and theoretical deliberations underlying the choice of an appropriate method for uncertainty propagation, including (a) law of propagation of uncertainty (JCGM 100, JCGM 102), or (b) Monte Carlo method (JCGM 101, JCGM 102), or a Bayesian method (JCGM 108). Such examples are urgently needed to aid the user of the cited guidance documents to make an informed choice. This WP2 is therefore strongly related to the GUM New Perspective.

Effect of pixel/voxel size on uncertainty associated with tumour volume or nanoparticle size

Factors that dictate choice of method will be brought out in many examples, including examples in which:

  • The law of propagation of uncertainty and a Monte Carlo method are compared for the quantification of low masses of benzo[a]pyrene.
  • Sample measurements of contaminants in soil are examined using several approaches to show how limited knowledge can be used most efficiently.
  • The adequacy of a straight-line function in calibrating sonic nozzles is considered against more general polynomial functions.
  • Analysis-of-variance approaches are applied to reference material production and certification in the case of gas mixtures, illustrating the advantages in using Bayesian methods over classical statistics.
  • GUM and Bayesian-based approaches are contrasted in two examples related to very small volume and flow.

Contaminants in soil: effect of sampling and measurement variability


Image of syringe being filled

Administration of ephedrine (stimulant): laboratory testing