Providing coverage of stachastic processes for undergraduate and postgraduate courses, this work includes an early chapter on computer simulation, which develops an understanding of Markov chains and processes. The text focuses on how to apply probability and stochastic processes to business and engineering problems, and demonstrates the range of possible applications for stochastic processes.
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amazon.con Customer Reviews on 1st edition:
5.0 out of 5 stars It's worth at least six stars!, February 19, 2000
By Lisa Ann Ball (Seattle, WA United States) - See all my reviews
I randomly ran across this book in my math library trying to find an extra book to help with the difficult Stochastics Process class I was taking. Little did I know I would find a book I value as much as Douglas Kelly's Introduction to Probability. This book has applied problems and examples! It is not the dry, endless pages of confusing equations we have come to expect from Stochastics Processes books. There is something better out there! This book saved me as an undergraduate, and am now looking forward to it living up to my God like expectations as a post grad. If you are a professor, please use this book for you students. It ties together and lets you appreciate many fields such as linear analysis and even graph theory from computer science. This book will not disappoint.
5.0 out of 5 stars Best introductory book, February 22, 2001
By Brad (Austin, TX USA) - See all my reviews
Extremely clear, and easy to understand. It is the best introductory book on stochastic processes for non-mathematics major. After you read this book (one month is enough, how amazing it is!), it becomes easier to read "the first course in stochastic processes". The book focuses on the concept and intuition, instead of proof, and I find it is extremely useful for me -- CS major.
Strong recommend this great book
5.0 out of 5 stars Good book! , August 13, 2007
By Yuan J. Son (sunnyvale, CA) - See all my reviews
A lot of examples, easy to read. A lot of stochastic and queuing books are usually full of notations and theorems, thus hard to understand. However, the author of this book presented the materials in a way that we can actually understand the stochastic processes. If you want to learn queuing and do not have much background, this is the book!!!!
Richard M. Feldman is a Professor of Industrial and Systems Engineering at Texas A&M University. He received a B.A. degree in mathematics from Hope College, an M.S. degree in mathematics from Michigan State University, an M.S. degree in Industrial and Systems Engineering from Ohio University, and a Ph.D. in Industrial Engineering from Northwestern University. His teaching interests include simulation, applied probability, and queueing theory. His consulting and funded research activities have involved modeling and simulation within manufacturing, transportation, and biological contexts. He has received several teaching awards, published papers in applied probability and queueing theory, and co-authored four books.
Ciriaco Valdez-Flores is senior risk assessment consultant at Sielken & Associates Consulting, Inc. He received a bachelor’s degree from the Tecnológico at Cd. Victoria in México and master’s and Ph.D. degrees from Texas A&M University, all in Industrial Engineering. He has taught graduate courses at Texas A&M University focusing in the areas of operations research and applied stochastic processes. As a consultant, he applies his background to the development of new methods of quantitative health risk assessment that incorporate simulation and decision tree theory. He has published in health risk assessment and stochastic processes, co-authored one book and has contributed to books in engineering economy and risk assessment.
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