The example describes how the measurement uncertainty of the calibration of a 10 kg weight can be performed using Bayes’ rule and a measurement model. The purpose of the example is to demonstrate how Bayes’ rule can be implemented in the context of the Guide to the expression of Uncertainty in Measurement and the uncertainty can be propagated. Special attention is paid to the assignment of probability density functions of type A and type B evaluations of standard uncertainty. The files contained in the dataset are: Readme.txt: instructions on how to install and run the project Mass_example_EA_4_02.pdf: Report "Bayesian evaluation of the mass calibration example from EA 4/02" Compendium.bib: bibliography file Mass_example_EA_4_02_Article.Rproj: RStudio project file Mass_example_EA_4_02.Rnw: source file to generate Mass_example_EA_4_02.tex in RStudio Mass_example_EA_4_02.bbl: file generated when compiling Mass_example_EA_4_02.tex Mass_example_EA_4_02.log: file generated when compiling Mass_example_EA_4_02.tex Mass_example_EA_4_02.synctex.gz: file generated when compiling Mass_example_EA_4_02.tex Mass_example_EA_4_02.tex: LaTeX file to be compiled in order to produce Mass_example_EA_4_02.pdf Mass_example_EA_4_02-concordance.tex: file generated by RStudio when compiling Mass_example_EA_4_02.Rnw.

This example was produced in the frame of the EMPIR project 17NRM05 Examples for evaluating measurement uncertainty.