[Encyclios]

Uncertainty estimation procedure

The uncertainty estimation procedure, i.e. error estimation, from a practical point of view requires:

• Specification of the measurand, i.e., clear and unambiguous definition of what is being measured;
• Definition of the mathematical model, i.e. definition of the relationship that links the measurand to the quantities determined by the measurement procedure chosen;
• Identification of the sources of uncertainty; there are various techniques, from the compilation of a structured list, to the use of cause-effect diagrams; the effect of several sources can be evaluated cumulatively;
• Quantification of uncertainty components; it is generally sufficient to quantify only the most important sources. Category A uncertainties are estimated as standard deviations from experimental data distributions; category B uncertainties must be derived from existing data and must be expressed and treated as standard deviations;
• Combining uncertainty components: all uncertainty components must be converted into standard uncertainties;
• Compounding the standard uncertainty; the expanded uncertainty will be calculated from the latter by applying the coverage factor.