Work

On the role of probability in science, analytical measurement and QUAM

Year: 2025

Type: article

Abstract: Recently, it has been shown that a probability distribution attributed to a constant, e.g. the true concentration of an analyte, cannot be used to accurately describe an objective set of information about the constant (Measurement Sensors 24, 2022, 100416; Accreditation and Quality Assurance 29, 2024, 189–192). In this paper, that result is extended to show that such a distribution cannot always accurately describe subjective belief about it either. These results suggest that a logical system of uncertainty analysis in measurement can only be based on classical principles in which probability distributions describe patterns of measurements and errors under repetition. They call into question the premise underlying the approach to the evaluation of measurement uncertainty promoted in the supplements to the Guide to the Expression of Uncertainty in Measurement. The relevance of these results to the Eurachem/CITAC Guide Quantifying Uncertainty in Analytical Measurement (QUAM) is discussed, and QUAM is shown to be largely free of the problematic idea.

Source: Accreditation and Quality Assurance

DOI: 10.1007/s00769-025-01631-3

Author: R. Willink

Institutions: Measurement Standards Laboratory of New Zealand, University of Otago

Language: English

Topic: Scientific Measurement and Uncertainty Evaluation

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,890

Funder: University of Otago