Simulation / Edition 5

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Sheldon Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer scientists, and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers can apply results of these analyses to problems in a wide variety of fields in order to obtain effective, accurate solutions, and to make predictions about future outcomes.

Audience: Researchers and practitioners in Computer Science, Industrial Engineering, Operations Research, Statistics, Mathematics, Electrical Engineering, Quantitative Business Analysis.

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Editorial Reviews

From The Critics
In the old days, says Ross (industrial engineering and operations research, U. of California-Berkeley), scientists formulating a stochastic model had to compromise between one that realistically portrayed the situation and one that could be comprehended mathematically. No more, he explains, now that fast and powerful computers are available cheap. He shows how to construct a model as faithful as possible to the phenomenon, then analyze it using a simulation study. He includes exercises for course study, but does not specify prerequisites. There's no mention of the dates of earlier editions. Annotation c. Book News, Inc., Portland, OR (
From the Publisher
“...It is outstanding because it is what it is and no other textbook out there does this job.”
- Kris Ostaszewski, Illinois State University

“Examples are infinitely more interesting than in almost any other book! Ross always explains clearly, I especially enjoy the exposition of the brand new sections” - Matt Carlton, Cal Polytechnic Institute

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Product Details

  • ISBN-13: 9780124158252
  • Publisher: Elsevier Science
  • Publication date: 11/1/2012
  • Edition number: 5
  • Pages: 328
  • Sales rank: 751,177
  • Product dimensions: 6.10 (w) x 9.10 (h) x 0.90 (d)

Meet the Author

Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.

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Table of Contents

1 Introduction 1
2 Elements of probability 5
3 Random numbers 41
4 Generating discrete random variables 49
5 Generating continuous random variables 67
6 The discrete event simulation approach 93
7 Statistical analysis of simulated data 117
8 Variance reduction techniques 137
9 Statistical validation techniques 219
10 Markov chain Monte Carlo methods 245
11 Some additional topics 273
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