Introduction to Probability Models

by Sheldon M. Ross

Introduction to Probability Models, Ninth Edition, is the primary text for a first undergraduate course in applied probability. This updated edition of Ross's classic bestseller 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. This book now contains a new section on compound random variables that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions; a new section on hiddden Markov chains, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states; and a simplified approach for analyzing nonhomogeneous Poisson processes. There are also additional results on queues relating to the conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system; inspection paradox for M/M/1 queues; and M/G/1 queue with server breakdown. Furthermore, the book includes new examples and exercises, along with compulsory material for new Exam 3 of the Society of Actuaries. This book is essential reading for professionals and students in actuarial science, engineering, operations research, and other fields in applied probability. A new section (3.7) on COMPOUND RANDOM VARIABLES, that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions.A new section (4.11) on HIDDDEN MARKOV CHAINS, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states.Simplified Approach for Analyzing Nonhomogeneous Poisson processesAdditional results on queues relating to the (a) conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system,;(b) inspection paradox for M/M/1 queues(c) M/G/1 queue with server breakdownMany new examples and exercises.

Genres: Mathematics, Textbooks, Science, Nonfiction, Reference

800 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.

[Mohamed Al-Emam]

college related