Probability, Statistics, and Queueing Theory

Probability, Statistics, and Queueing Theory

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Description

This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edition includes a new chapter on regression as well as more than twice as many exercises at the end of each chapter. While the emphasis is the same as in the first edition, this new book makes more extensive use of available personal computer software, such as Minitab and Mathematica.
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Product details

  • Hardback | 768 pages
  • 162.56 x 236.22 x 45.72mm | 1,247.37g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 2nd edition
  • 0120510510
  • 9780120510511

Table of contents

Introduction. Probability. Probability and Random Variables. Probability Distributions. Stochastic Processes. Queueing Theory. Queueing Theory. Queueing Models of Computer Systems. Statistical Inference. Estimation and Data Analysis. Hypothesis Testing. Regression. Appendices. Statistical Programs. APL Programs. Queueing Theory Definitions and Formulas. Mathematica Programs. Answers to Exercises.
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About Arnold O. Allen

Arnold O. Allen is a member of the technical staff of the Performance Technology Center at Hewlett-Packard. He received his Ph.D. in mathematics from UCLA. Much of the material in the book was developed for classes in probability, statistics, queueing theory, and computer modeling that he taught as UCLA, IBM, and Hewlett-Packard. Dr. Allen has been active in teaching conference tutorials on computer modeling and was the keynote speaker at two international conferences.
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Review quote

"Allens book is a most welcome contribution: it is self-contained, well-focused and replete with instructive examples. Its informal style makes it well-suited for the non-academic practitioner, but it is also an excellent text for advanced undergraduates."
--COMPUTING REVIEWS
"The techniques and methodology for evaluating computer system performance and capacity are nicely described in Dr. Allen's excellent book. The use of computer-oriented examples is instructive as well as refreshing."
--IBM SYSTEMS JOURNAL
"The exposition and notation are unusually clear...this is a well executed, useful book which should be in every computer scientist's library."
--POPULAR COMPUTING
"This book covers just enough theory so that the practical aspects can be illustrated. Homework mixed with humor further strengthens queueing applications. Over the last decade my graduate students, 95% of whom are now practicing engineers in industry, keep telling me how useful [the book] is as a reference..."
--Monte Ung, UNIVERSITY OF SOUTHERN CALIFORNIA
"I have used the text in a two-semester course in Probability and Stochastic Processes at George Mason University. I chose the text because of its complete coverage of these subjects and its organization of topics. I particularly appreciated its up-front introduction of important concepts like joint and conditional distributions and transform methods. These concepts are then exploited in the subsequent development of discrete and continuous distributions and limit theorems. The treatment of stochastic processes and queueing theory was exactly what I wanted for my O.R.-oriented audience. the book was very complete and clear in its explanations, and it includes many excellent examples and exercises. I was quite pleased with my class's success with this text, and I am looking forward to using the new edition."
--Donald T. Gantz, Ph.D., GEORGE MASON UNIVERSITY
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11 ratings
4.18 out of 5 stars
5 36% (4)
4 45% (5)
3 18% (2)
2 0% (0)
1 0% (0)
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