Introduction to Probability Models

by Sheldon M. Ross

This best-selling reference is well-suited to those seeking to apply probability theory to phenomena in such fields as engineering, actuarial and management sciences, the physical and social sciences, and operations research. Realistic models of real-world phenomena must take into account the possibility of randomness. More often than not, quantities are not predictable, but exhibit variations that should be taken into account by the model. This is usually accomplished by allowing the model to be probabilistic in nature. Such a model is referred as a probability model. Introduction to Probability Models is a fascinating introduction to applications from diverse disciplines and an excellent introduction to a wide variety of applied probability topics. * Best-selling book by a well-known author, with over 20,000 in sales for 7th edition * Includes new examples and exercises in actuarial sciences * Contains compulsory material for Exam 3 of the Society of Actuaries Author Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. He received his Ph.D. in statistics at Stanford University in 1968 and has been at Berkeley ever since. 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, Fourth Edition published by MacMillan, Introduction to Probability Models, Fifth Edition published by Academic Press, Stochastic Processes, Second Edition published by Wiley, and a new text, Introductory Statistics published by McGraw Hill. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences published by Cambridge University Press. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.

Genres: Mathematics, Textbooks, Science, Nonfiction, Reference

544 pages, Hardcover

First published December 1, 1972

About the author

Sheldon M. Ross is the Epstein Chair Professor at the Department of Industrial and Systems Engineering, University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968 and was formerly a Professor at the University of California, Berkeley, from 1976 until 2004. He has published more than 100 articles and a variety of textbooks in the areas of statistics and applied probability, including Topics in Finite and Discrete Mathematics (2000), Introduction to Probability and Statistics for Engineers and Scientists, 4th edition (2009), A First Course in Probability, 8th edition (2009), and Introduction to Probability Models, 10th edition (2009), among others. Dr Ross serves as the editor for Probability in the Engineering and Informational Sciences.

Reviews

[Siah · Rating 5 out of 5]

I love this book with every cell in my body. Have read it so many times and every time learned something new. You cannot work in the industry without reading this.

[Alexander Bos · Rating 4 out of 5]

I have the same quibbles about this book as I have about the Probability Theory book of Sheldon Ross. The chapters are just too large, there have to be some more smaller easier exercises sprinkled in between them, especially considering its just an introduction text to the subject. It's just extremely difficult (at least for me) to grasp the concepts properly if I cannot test myself often enough.

Granted, I didn't finish the book, I finished 6/11 chapters, I may come back to the book if I need to. Its the only book I know that discusses various probability models, though one might be better of just studying books specifically talking about a certain probability model, like Queuing theory, or Markov Chains.

[Jonas Moss · Rating 1 out of 5]

One of the worst textbook I've used. He doesn't define terms properly, merge theorems and propositions with examples, and put far too much emphasis on the examples. If you want to learn Markov chain theory, use wikipedia instead.

[Ahmed Atif Abrar · Rating 2 out of 5]

Not exegetical like that of Jay L. Davore. Few examples added with the lack of immaterial exemplars have made it less accessible to neophytes to probability.

[dead letter office · Rating 3 out of 5]

a very basic and applied book on probability models. if it were me, i'd read drake's book on probability to get the basics and then go straight to a more advanced text on whatever you're interested in (markov chains or probability theory or stochastic processes or queuing theory or whatever) and skip this thing.

[Jette Stuart · Rating 5 out of 5]

I'll be honest this course was the stuff of nightmares for many of us in Stochastic Processes. This book along with the solutions manual made all the difference. Perfect for those who learn by example.

[Chayan Chang · Rating 5 out of 5]

An excellent and systematic introduction to elementary probability theory and stochastic processes.
This book is particularly helpful in demonstrating how probability theory can be applied across fields such as management science, social sciences, and operations research.

[Jette Stuart · Rating 4 out of 5]

Sheldon Ross is a genius of our time. This is an excellent book for introduction to stochastic processes, a subject that I am sure most find challenging.

[Jeremy Dwyer · Rating 5 out of 5]

Excellent treatment of all mathematical topics. One of my all time favorites.

[Zhuzi_20 · Rating 5 out of 5]

I've been waiting for a book to replace https://webspace.maths.qmul.ac.uk/b.j...
This is the book I've been looking for! Inside it will satisfy all my curiosity about probability proofs.

[Mohamed Al-Emam]

college related