Introduction to Probability Models
13th Edition
Published on 5. July 2023
Book
Paperback/Softback
870 pages
978-0-443-18761-2 (ISBN)
Description
*Textbook and Academic Authors Association (TAA) McGuffey Longevity Award Winner, 2024*
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.
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.
More details
Edition
13th edition
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Dimensions
Height: 227 mm
Width: 151 mm
Thickness: 43 mm
Weight
1424 gr
ISBN-13
978-0-443-18761-2 (9780443187612)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Sheldon M. Ross
Introduction to Probability Models
E-Book
06/2023
13th Edition
Academic Press
€106.00
Available for download
Previous edition
Sheldon M. Ross
Introduction to Probability Models
Book
05/2019
12th Edition
Academic Press
€103.98
Article exhausted; check for reprint
Person
Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD 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, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.
Content
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