An introduction to data modeling principles in metrology and testing

Abstract

The dispersion of the measured data introduces an uncertainty in the measure of the observed phenomena. Uncertainty associated with data is specified according to models that are different according to the underpinning assumptions, which must adequately match the characteristic of the observed phenomena or process. This chapter deals with the different types of description of the uncertainty components, with a wide selection of citations from reference international documents, and then with the different models corresponding to the different data characteristics. An extended bibliography is included.