All measurements are subject to error. When a reportable value is derived from a measurement or series of measurements, this value is only an estimate of the “true ...

Bayesian uncertainty analysis represents a powerful statistical framework that integrates prior knowledge with observed measurement data to quantify uncertainty in a consistent probabilistic manner.

In the first round of testing, involving 60 measurements (six samples x five repeat tests x two rounds), an initial review of the results indicated that one sample consistently performed better than ...

GUM, the internationally approved technique for calculating measurement uncertainty, is reliant on the availability of a certified reference sample. Likewise, to find any repeatable offset (systematic ...

A program for calibration and routine testing of weighing instruments ensures accurate results. A measurement of any kind is affected by the errors and uncertainties that exist in that measurement ...

In order to use the result of a chemical analysis for other purposes, its quality must be assessed. One important quality feature is the probability that the result coincides with the ‘true’ value. It ...

Measurements are always made for a reason – to answer a particular question or to help solve a problem. Whenever a measurement is made there will always be some uncertainty about the result due to ...

This two-day course gives an introduction to the theory and practice of calculating Uncertainty of Measurement for chemical analysis of foods. The approach to Uncertainty measurement will follow the ...

Ensuring parts meet specification is crucial and so it helps to have confidence in your measurement system. Parts that don’t meet specification, whether gauging composition or measuring thickness, ...