by Michael S. Hamada, Alyson G. Wilson, C. Shane Reese, Harry F. Martz

Chapter 2

Bayesian Inference

In this chapter we review the fundamental concepts of Bayesian and likelihood-based inference in reliability. We explore prior distributions, sampling distributions, posterior distributions, and the relation between the three quantities as specified through Bayes’ Theorem. We also provide examples of inference in both discrete and continuous settings.

Solutions to Chapter 2 Exercises

Chapter 2 Data Sets