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.

Performing a measurement uncertainty calculation is often seen as problematic. One of the barriers to be overcome in the wider application of measurement uncertainty (MU) to reportable values is the ...

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 ...

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 ...

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 ...

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, ...

Mettler Toledo offers a new and unique service to titration customers, the Measurement Uncertainty Pac (MuPac), part of the Good Titration Practice™ Secure service offerings. MuPac offers a detailed ...

With today's applications requiring lower and lower noise-figure amplifiers, noise-source uncertainty becomes a bigger and bigger concern. Microwave modeling software ...