By reducing mathematical detail and focusing on real-world
applications, this book provides engineers with an
easy-to-understand overview of stochastic modeling. An entire
chapter is included on how to set up the problem, and then another
complete chapter presents examples of applications before doing any
math. A previously unpublished computational method for solving
equations related to Markov processes is added. The book shows how
to add costs or revenues to the basic probability structures
without much additional effort. In addition, numerous examples are
included that show how the theory can be used. Engineers will also
find explanations on how to formulate word problems into the models
that the math worked on.
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