Chapter 1 Basic formal concepts

We introduce formal concepts in Bayesian inference starting with the Bayes’ rule, all its components with their formal definitions and basic examples. In addition, we present some nice features of Bayesian inference such as Bayesian updating, and asymptotic sampling properties, and the basics of Bayesian inference based on decision theory under uncertainty, presenting important concepts like loss function, risk function and optimal rules.