Abstract
In this section we review the main Probability operators that are strongly
associated with the main themes of this book which are Discrete-Time Markov
Chain Process, and Continuous-Time Markov Chain Process. the chapter begins
with the basic definition of: certain event, dependent event, independent event and
impossible event. Later we review the concept of conditional probability which
permeates all the following chapters as well as the multiplication rule. At the end
the Bayes’ Theorem is addressed which is the basis of the procedures described in
the last chapters as they are: Discrete and Continuous-Time Markov Chain Process.
All sections are exemplified in the simplest and most complete way possible, so that
the reader does not have difficulty in the use and language of these operators in the
following sections.