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Linear Models in the Presence of Type B Uncertainty:A Bayesian View of Annex H.3 and H.5 of the Guide to the Expression of Uncertainty in Measurement

Published

Author(s)

Blaza Toman

Abstract

Annex H.3 of the Guide to the Expression of Uncertainty in Measurement presents an example of calibration of a thermometer using a linear regression model. Annex H.5 of the same publication presents a class of statistical models and analysis techniques which are commonly called the Analysis of Variance (ANOVA). These models are useful for accounting for the effects of factors which cause the measurand in an experiment to change over time or over experimental conditions. Both Annex H.3 and H.5 present procedures which assume that the observations are not subject to type B uncertainties. A natural question then is: Can these models be used in the presence of type B uncertainties? This article answers the question in the affirmative and provides a natural interpretation of the results. The example data from the two Annexes are used for an illustration.
Citation
Metrologia

Keywords

analysis of variance, Bayesian statistics, linear regression, type B uncertainty

Citation

Toman, B. (2006), Linear Models in the Presence of Type B Uncertainty:A Bayesian View of Annex H.3 and H.5 of the Guide to the Expression of Uncertainty in Measurement, Metrologia (Accessed March 2, 2024)
Created February 1, 2006, Updated February 17, 2017