Probability and Random Processes

by Geoffrey R. Grimmett, David R. Stirzaker

This third edition of this successful text gives a rigorous and extensive introduction to probability theory and an account in some depth of the most important random processes. It includes various topics which are suitable for undergraduate courses, but are not routinely taught. It is suitable for students of probability at all levels. There are four main 1) to provide a thorough but straightforward account of basic probability, giving the reader a natural feel for the subject unburdened by oppressive technicalities, 2) to discuss important random processes in depth with many examples. 3) to cover a range of important but less routine topics, 4) to impart to the beginner the flavour of more advanced work. The book begins with basic ideas common to many undergraduate courses in mathematics, statistics and the sciences; it concludes with topics usually found at graduate level. The ordering and numbering of material in this third edition has been mostly preserved from the second. Minor alterations and additions have been added for clearer exposition. Highlights include new sections on sampling and Markov chain Monte Carlo, geometric probability, coupling and Poisson approximation, large deviations, spatial Poisson processes, renewal-reward, queuing networks, stochastic calculus, Ito's formula and option pricing in the Black- Scholes model for financial markets. In addition there are many (nearly 400) new exercises and problems that are entertaining and instructive; their solutions can be found in the companion volume 'One Thousand Exercises in Probability', (OUP).

Genres: Mathematics, Textbooks, Reference, Science

608 pages, Hardcover

First published September 1, 1982

Reviews

[Nick Black · Rating 3 out of 5]

Our book for MATH 3220 -- Honors Probability and Statistics. While it's just as poorly written as any other undergraduate stochastics book, it's at least got very thorough coverage and a basis in rigorous measure theory. If you're not using measure theory, you're not doing probability, and should slowly back away from the model until you've integrated the Lebesgue into your gestalt.

[Ludwig · Rating 3 out of 5]

a good book which covers maths of probability and random variable.

I borrowed from the library because I was doing MCMC lab. Unfortunately, it turned out I didn't manage to do a good job because I got too much to (re)learn in two weeks and I was in bad mood. So today's challenge was to finish this book on the train - nice/shamful to see how little I know and how much I have to learn!

[Elchin Jafarov · Rating 4 out of 5]

Very good book but definetly not for beginners. If you want to enjoy reading and studying this one, first consider learning from more introductory books in probability and statistics.

[Qubitng · Rating 4 out of 5]

Far too difficult as a standard course in undergraduate probability. Some of the exercises have an indulgent/non-instructive feel to them; for example, the very first exercise in section 4.14 is to find \int^{\infty}_{-\infty} e^{-x^2} dx. No hint provided. Seriously? This exercise has no instructive purpose other than to force you to look the answer up if you don't already know the trick.

Instead the breadth of topics and the extensive number of exercises make this book worthwhile for grad students and advanced undergrads. 4 stars (0.5 stars if used as first course in undergrad probability).

[dead letter office · Rating 3 out of 5]

the best intro graduate level text i know on probability (and it's not really that great).

[Jeff · Rating 3 out of 5]

The content is good, but dense, particularly if it's your first introduction to probability. Should definitely get the companion book containing all the exercises and their solutions.