Calibration and Statistical Inference

Abstract

This article presents an elementary statistical model from which inferences in the form of probability statements are drawn. These are compared with the inferences derived from the corresponding classical and Bayesian models of the same phenomenon. The example concerns a measuring device, and the problem of calibration is discussed. The method of analysis extends to a wide range of common statistical applications, notably those described by multivariate and linear regression models.