ABSTRACT
Chapter 7 builds upon concepts developed in Chapters 2–4 and introduces the reality of uncertainty and randomness that is all around us and that we must take in account during the modeling process. This chapter focuses on explicitly representing this uncertainty in our mathematical models. We will introduce some of the most important and commonly used stochastic models to include Markov chains, transition matrices, and Bayes’ Theorem.
