1. Goals and constraints of statistical inference

1.1 Formalism

Before setting out the elements needed to build a Bayesian inferential machine, we first consider the essential points that define statistical science. Its fundamental aim is to take observations of a random phenomenon and make an inference, i.e. a logical deduction about the probabilistic mechanism leading to this phenomenon. The ultimate aim of this methodology is to provide an analysis (or description) of a past phenomenon, or a forecast of a future phenomenon (of the same nature).