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
Preț: 562.67 lei
Preț vechi: 847.64 lei
-34% Nou
Puncte Express: 844
Preț estimativ în valută:
99.58€ • 116.78$ • 87.31£
99.58€ • 116.78$ • 87.31£
Carte tipărită la comandă
Livrare economică 19 ianuarie-02 februarie 26
Livrare express 19-25 decembrie pentru 129.26 lei
Preluare comenzi: 021 569.72.76
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
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