NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.
Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.
An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Assessing differences between results determined according to the Guide to the Expression of Uncertainty in Measurement
Published
Author(s)
Raghu N. Kacker, Ruediger Kessel, Klaus-Dieter Sommer
Abstract
When the data consist of multiple results of measurement for a common measurand, often one needs to determine whether the results agree with each other. A result of measurement based on the Guide to the Expression of Uncertainty in Measurement (GUM) consists of a measured value together with its associated standard uncertainty. In the GUM, the measured value is regarded as the expected value and the standard uncertainty is regarded as the standard deviation, both known values, of a state-of-knowledge probability distribution. A state-of-knowledge distribution represented by a result is not required to be completely known. Then how can one assess the differences between the results based on the GUM? Metrologists have for many years used the Birge chi-square test as a rule of thumb to assess the differences between two or more measured values for the same measurand by pretending that the standard uncertainties were the standard deviations of the presumed sampling probability distributions from random variation of the measured values. We point out that this is misuse of the standard uncertainties; the Birge test and the concept of statistical consistency motivated by it do not apply to the results of measurement based on the GUM. In 2008, the International Vocabulary of Metrology, third edition (VIM3) introduced the concept of metrological compatibility. We show that the concept of metrological compatibility can be used to assess the differences between results based on the GUM for the same measurand. A pairwise Birge test of statistical consistency and a test of metrological compatibility do not conflict.
Kacker, R.
, Kessel, R.
and , K.
(2010),
Assessing differences between results determined according to the Guide to the Expression of Uncertainty in Measurement, Journal of Research (NIST JRES), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=906548
(Accessed October 2, 2025)