Product Description

Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Third Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems.

* Realistic applications from a variety of disciplines integrated throughout the text
* Plentiful, updated and more rigorous problems, including computer "challenges"
* Revised end-of-chapter exercises setsin all, 250 exercises with answers
* New chapter on Brownian motion and related processes
* Additional sections on Matingales and Poisson process
* Solutions manual available to adopting instructors

Product Details

• Amazon Sales Rank: #305264 in Books
• Published on: 1998-02
• Number of items: 1
• Binding: Hardcover
• 631 pages

Review
PRAISE FOR THE SECOND EDITION
"This book is a valuable resource for anyone studying combustion processes."
--David L. Liscinsky, United Technologist Research Center, in AIAA JOURNAL
"This is an excellent text-book....The narrative is clear, careful and detailed but, at the same time, designed to draw (not to bore) the reader in. The main strengths, in my opinion, are the wealth of convincing applications, which are discussed at some, but not too much length after each bit of theoretical development, and the large number of exercises given at the ends of sections, not just at the ends of chapters."
--Martin Crowder, University of Surrey, Guildford, in THE STATISTICIAN

Review
PRAISE FOR THE SECOND EDITION
"This book is a valuable resource for anyone studying combustion processes."
--David L. Liscinsky, United Technologist Research Center, in AIAA JOURNAL
"This is an excellent text-book....The narrative is clear, careful and detailed but, at the same time, designed to draw (not to bore) the reader in. The main strengths, in my opinion, are the wealth of convincing applications, which are discussed at some, but not too much length after each bit of theoretical development, and the large number of exercises given at the ends of sections, not just at the ends of chapters."
--Martin Crowder, University of Surrey, Guildford, in THE STATISTICIAN

About the Author
Howard E. Taylor is a research chemist with the National Research Program, Water Resources Division, U.S. Geological Survey located in Boulder, Colorado. Dr. Taylor has played a major role over the past 25 years in the development of plasma spectrometric techniques in analytical chemistry, as reflected in his more than 150 technical publications and the presentation of numerous papers at national and international technical meetings. He has served as faculty affiliate at Colorado State University and has taught American Chemical Society Short Courses for more than 15 years.

Customer Reviews

good applied stochastic processes book
Since the third edition is out and I have not seen I must say upfront that my comments are on an earlier edition. This pair of authors have done an excellent job with three textbooks on stochastic processes. Unlike the other two books that give a rigorous treatment of stochastic processes this book is more applied with the emphasis on examples and models for real applied problems. Introductory probability and statistics is assumed by the authors and they deal with all the standard topics.

However, I do have to agree with the other reviewers who criticize the organization. Karlin and Taylor are not known for great organizational skills. Sometimes that is a trait of a mathematical genius. Sam Karlin can certainly be put into that category. Although I never took a course from him at Stanford, the fact that he was a Stanford professor meant that I did learn a lot about him and see him on campus and hear an occasional lecture. Of course this was a long time ago in the mid 1970s when the first edition of the first course was out and the other two books had probably not yet been contemplated.

In any case this would be a good reference for an applied statistician to have.

Dive into the deep end... or atleast pretend you are...
This book opens with a nose dive into Conditional probability. Unlike some other authors that devote a half their entire bloody book on review of probability, random variables, and conditional probability distributions, this book assumes a firm or atleast an introductory knowledge of the above. Ideally, a good probability book such as Hogg and Tanis would prove to be quite helpful as a supplementary reference.

Markov Chains and Processes are introduced in the third chapter and the definition is lucid, complete with examples that are easy to comprehend. One of the examples that calculated the frequency with which an autoparts store must replenish its stock was absolutely brilliant and made things a lot easier to understand. The exercises are rather thorough, so if you are purchasing this book for a class and will be assigned homework assignments from the text, be prepared to devote atleast an hour on an average to each problem.

The book is relatively easy to read, if you have a good background in random variables, and hence, i repeat, keep a book on introductory probability and statistics handy.

Cheap Binding
Letting the other reviews critique the content, I would like to mention that I was unimpressed with the quality of the binding.

Although I may be a unique occurence, the binding of my book was cheap and broke so that several pages came loose. For an $80 book I expect better durability than a paperback.