Quantification of measurement uncertainty: basics, applications, trends

Carlo Carobbi, 4 hours, 1 CFU, June 2019

Quantification of measurement uncertainty (MU) is a required step of any measurement process. MU is necessary in order to compare the measurement result with another measurement result, a mathematical model, a simulation result, a tolerance interval or limit and to take a decision on the basis of agreement/disagreement, compliance/non-compliance. Quantification of MU is a scientific activity based in part based on standard procedures and in part on the competence and experience of the expert who performs the quantification. The scope of this lecture is to introduce the students to quantification of MU, focusing on applications to electrical and radiofrequency measurements. Future trends in the evaluation of measurement uncertainty will be highlighted and references will be given in order to provide students with the essential tools for elaborating these concepts.

Students attending this lecture will be able to: 

  •  Use the correct metrological concepts and terminology, as defined in the International Vocabulary of Metrology;
  • Formulate the measurement model equation;
  • Assign the appropriate probability density function to the measurement model input quantities;
  • Either propagate standard uncertainties or probability density functions through the measurement model (depending on the applicability of the Central Limit Theorem);
  • Determine the coverage interval of the output quantity.

Duration: 4 hours (1 credit)

Date: June 27-28, 2019, Time: 10:30 – 12:30


1. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, 2008 Guide to the Expression of Uncertainty inMeasurement, JCGM 100:2008, GUM 1995 with minor corrections, www.bipm.org/utils/common/documents/jcgm/JCCGM 100 2008 E.pdf

2. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, 2008 Supplement 1 to the ‘Guide to the Expression of Uncertainty in Measurement’—Propagation of distributions using a Monte Carlo method JCGM 101:2008, www.bipm.org/utils/common/documents/jcgm/JCGM 101 2008 E.pdf

3. I. Lira, Evaluating the Measurement Uncertainty – Fundamentals and Practical Guidance, First edition, Institute ofPhysics Publishing, London (UK), 2002.

4. NIST Uncertainty Machine, Web-based software application available at http://uncertainty.nist.gov/