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

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 ...

Monte Carlo methods have emerged as a crucial tool in the evaluation of measurement uncertainty, particularly for complex or non-linear measurement systems. By propagating full probability ...

The technique which is recommended by the regulatory bodies ISO (International Organisation for Standardisation) and BIPM (Bureau International des Poids et Mesures) is one of the most comprehensive ...

Measurement uncertainty, as described in ISO/IEC Guide 98, is a “parameter, associated with the result of a measurement, [which] characterizes the dispersion of values that could reasonably be ...

Precision can be defined as the closeness in agreement of results during a series of repeat measurements under presumed identical conditions. These results are often expressed as a standard deviation.

Based on the EURAMET Calibration Guide No. 18 “Guidelines on the Calibration of Non-Automatic Weighing Instruments” 1–3 (represented as “EURAMET cg-18”), this QApp function offers a dynamic display of ...

Although most modern organisations possess extensive data, a subtler challenge persists: a lack of understanding regarding ...