Introduction to Bayesian analysis

Bayesian methods provide a useful tool for statistical inference under an uncertainty environment. Incorporating a scientific hypothesis, Bayesian methods introduced a new interpretation of “probability” as a rational, conditional measure of uncertainty. This chapter covers basic notions of Bayesian analysis, including Bayes’ theorem, prior, posterior, predictive, densities, etc. In the next section, we discuss the concept of probability.