Introduction to probability models

✍ Scribed by Ross, Sheldon M

• Publisher: Elsevier,Academic Press
• Year: 2010
• Tongue: English
• Leaves: 801
• Edition: 10ed.
• Category: Library

✦ Synopsis

Ross's classic bestseller, Introduction to Probability Models, 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. 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.  Read more...

Abstract:

Suitable for a first undergraduate course in applied probability, this book introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, computer science, management science, the physical and social sciences, and operations research.  Read more...

✦ Table of Contents

Content: Preface --
Introduction to Probability Theory
--
Random Variables --
Conditional Probability and Conditional Expectation --
Markov Chains --
The Exponential Distribution and the Poisson Process --
Continuous-Time Markov Chains --
Renewal Theory and Its Applications --
Queueing Theory --
Reliability Theory --
Brownian Motion and Stationary Processes --
Simulation --
Appendix: Solutions to Starred Exercises --
Index.

✦ Subjects

Probabilities.