Introduction to Probability Models
Autor Sheldon M. Rossen Limba Engleză Paperback – 5 iul 2023
A trusted market leader for four decades, Sheldon Ross’s Introduction to Probability Models offers a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Through its hallmark exercises and real examples, this valuable course text
Introduction to Probability Models provides the reader with a comprehensive course in the subject, from foundations to advanced topics.
- Winner of a 2024 McGuffey Longevity Award (College) (Texty) from the Textbook and Academic Authors Association
- Retains the useful organization that students and professors have relied on since 1972
- Includes new coverage on Martingales
- Offers a single source appropriate for a range of courses from undergraduate to graduate level
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (1) | 546.49 lei 5-7 săpt. | +78.65 lei 7-13 zile |
| ELSEVIER SCIENCE – 5 iul 2023 | 546.49 lei 5-7 săpt. | +78.65 lei 7-13 zile |
| Hardback (1) | 608.98 lei 6-8 săpt. | |
| ELSEVIER SCIENCE – 4 mar 2014 | 608.98 lei 6-8 săpt. |
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Specificații
ISBN-13: 9780443187612
ISBN-10: 0443187614
Pagini: 870
Dimensiuni: 152 x 229 x 44 mm
Greutate: 1.18 kg
Ediția:13
Editura: ELSEVIER SCIENCE
ISBN-10: 0443187614
Pagini: 870
Dimensiuni: 152 x 229 x 44 mm
Greutate: 1.18 kg
Ediția:13
Editura: ELSEVIER SCIENCE
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Cuprins
1. Introduction to Probability Theory
2. Random Variables
3. Conditional Probability and Conditional Expectation
4. Markov Chains
5. The Exponential Distribution and the Poisson Process
6. Continuous-Time Markov Chains
7. Renewal Theory and Its Applications
8. Queueing Theory
9. Reliability Theory
10. Brownian Motion and Stationary Processes
11. Simulation
12. Coupling
13. Martingales
2. Random Variables
3. Conditional Probability and Conditional Expectation
4. Markov Chains
5. The Exponential Distribution and the Poisson Process
6. Continuous-Time Markov Chains
7. Renewal Theory and Its Applications
8. Queueing Theory
9. Reliability Theory
10. Brownian Motion and Stationary Processes
11. Simulation
12. Coupling
13. Martingales
Recenzii
"The hallmark features of this renowned text remain in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics…new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data." --Zentralblatt MATH 1284-1
"…the newest edition updated with new examples and exercises, actuarial material, Hawkes and other point processes, Brownian motion, and expanded coverage of Markov chains. Although formally rigorous, the emphasis is on helping students to develop an intuitive sense for probabilistic thinking."--ProtoView.com, April 2014
Praise from Reviewers for the 10th edition:"I think Ross has done an admirable job of covering the breadth of applied probability. Ross writes fantastic problems which really force the students to think divergently...The examples, like the exercises are great." --Matt Carlton, California Polytechnic Institute"This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book." --Jean LeMaire, University of Pennsylvania"This book may be a model in the organization of the education process. I would definitely rate this text to be the best probability models book at its level of difficulty...far more sophisticated and deliberate than its competitors." --Kris Ostaszewski, University of Illinois
"…the newest edition updated with new examples and exercises, actuarial material, Hawkes and other point processes, Brownian motion, and expanded coverage of Markov chains. Although formally rigorous, the emphasis is on helping students to develop an intuitive sense for probabilistic thinking."--ProtoView.com, April 2014
Praise from Reviewers for the 10th edition:"I think Ross has done an admirable job of covering the breadth of applied probability. Ross writes fantastic problems which really force the students to think divergently...The examples, like the exercises are great." --Matt Carlton, California Polytechnic Institute"This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book." --Jean LeMaire, University of Pennsylvania"This book may be a model in the organization of the education process. I would definitely rate this text to be the best probability models book at its level of difficulty...far more sophisticated and deliberate than its competitors." --Kris Ostaszewski, University of Illinois
Notă biografică
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.
Descriere
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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.