Introduction to Probability Models, 10th Edition Front Cover

Introduction to Probability Models, 10th Edition

  • Length: 800 pages
  • Edition: 10
  • Publisher:
  • Publication Date: 2009-12-17
  • ISBN-10: 0123756863
  • ISBN-13: 9780123756862
  • Sales Rank: #860803 (See Top 100 Books)
Description

Ross’s classic bestseller, Introduction to Probability Models, tenth Edition has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries.

Ancillary list:

  • Instructor’s Manual – http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123743886
  • Student Solutions Manual – http://www.elsevierdirect.com/product.jsp?isbn=9780123756862#42
  • Sample Chapter, eBook – http://www.elsevierdirect.com/product.jsp?isbn=9780123756862

New to this Edition:

  • 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains
  • Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams
  • Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, test bank, and companion website
  • Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field

Hallmark features:

  • Superior writing style
  • Excellent exercises and examples covering the wide breadth of coverage of probability topics
  • Real-world applications in engineering, science, business and economics

Table of Contents

Chapter 1. Introduction to Probability Theory
Chapter 2. Random Variables
Chapter 3. Conditional Probability and Conditional Expectation
Chapter 4. Markov Chains
Chapter 5. The Exponential Distribution and the Poisson Process
Chapter 6. Continuous-Time Markov Chains
Chapter 7. Renewal Theory and Its Applications
Chapter 8. Queueing Theory
Chapter 9. Reliability Theory
Chapter 10. Brownian Motion and Stationary Processes
Chapter 11. Simulation
Appendix: Solutions to Starred Exercises

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