3. Taking "a priori" factors into account (Bayesian approach)

The aim of this approach is to construct the probability law of possible true values. This law of probability is fundamentally different from the law of dispersion of measurements. The law of dispersion of measurements is the law of probability of measurement values "knowing the true value". It describes a "frequentist" physical process. The probability law of possible true values is constructed "knowing one or more measurement values". There is frequent confusion between these two laws, as the same mathematical tools are used to construct them, namely "conditional" probability laws.

Schematically, in the Bayesian approach, the probability distribution of possible true values becomes the observer's "degree of belief". This degree of belief is modeled by a conditional probability density function that depends on the information available. This information is of two...