Based on a highly popular, well-established course taught by the authors, Stochastic Processes: An Introduction, Second Edition discusses the modeling and analysis of random experiments using the theory of probability. It focuses on the way in which the results or outcomes of experiments vary and evolve over time.

The text begins with a review of relevant fundamental probability. It then covers several basic gambling problems, random walks, and Markov chains. The authors go on to develop random processes continuous in time, including Poisson, birth and death processes, and general population models. While focusing on queues, they present an extended discussion on the analysis of associated stationary processes. The book also explores reliability and other random processes, such as branching processes, martingales, and a simple epidemic. The appendix contains key mathematical results for reference.

Ideal for a one-semester course on stochastic processes, this concise, updated textbook makes the material accessible to students by avoiding specialized applications and instead highlighting simple applications and examples. The companion website contains

*Mathematica*® programs that offer flexibility in creating graphs and performing computations.

Some Background on Probability | Some Gambling Problems | Random Walks | Markov Chains | Poisson Processes | Birth and Death Processes | Queues | Reliability and Renewal | Branching and Other Random Processes | Computer Simulations and Projects | Answers and Comments on End-of-Chapter Problems

Companion Website

Modeling and Simulation,

Probability and Statistics