Sunday, 02 March 2025

Time:
9:00 - 11:30 AM
Place:
t.b.a.
Presenter:
J. Meija, Ottawa (Canada)

Book your participation

Measurement uncertainty is the doubt that remains after making a measurement and this Short Course will introduce the essential tools used to evaluate this doubt – from the classical Gauss’s formula, non-parametric methods, Monte Carlo simulations, to modern Bayesian methods [1]. The evaluation of measurement uncertainty is often limited to calculating standard deviations, without taking into account the measurement models that describe how various sources of uncertainty interact. This Course will outline the fundamental building blocks for uncertainty evaluation reminding that the results of chemical measurements depend not only on calibration standards and measurement methods but also on a variety of statistical models employed [2]. Through numerous practical examples, all implemented in Excel, the course will explore a wide array of modern modeling options to provide a deeper understanding of how measurement uncertainties can be evaluated and to recognize that a larger statistical toolkit can lead to more reliable results.

References
1. A. Possolo, D.B. Hibbert, J. Stohner, O. Bodnar, J. Meija, Pure Appl. Chem. 2024; 96: 113-134.
2. J. Meija, A. Possolo. Measurement Uncertainty: A Reintroduction, 2nd ed. Sistema Interamericano de Metrologia – SIM: Montevideo, 2022.