**Probability: Theory and Examples**

by Rick Durrett

**Publisher**: Cambridge University Press 2010**ISBN/ASIN**: 0521765390**ISBN-13**: 9780521765398**Number of pages**: 372

**Description**:

This book is an introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action.

Download or read it online for free here:

**Download link**

(1.8MB, PDF)

## Similar books

**Recent Progress on the Random Conductance Model**

by

**Marek Biskup**-

**arXiv**

Recent progress on understanding of the Random Conductance Model is reviewed and commented. A particular emphasis is on the results on the scaling limit of the random walk among random conductances for almost every realization of the environment.

(

**5723**views)

**Lectures on Random Polymers**

by

**F. Caravenna, F. den Hollander, N. Petrelis**-

**arXiv**

These lecture notes are a guided tour through the fascinating world of polymer chains interacting with themselves and/or with their environment. The focus is on the mathematical description of a number of physical and chemical phenomena.

(

**8001**views)

**Foundations of Constructive Probability Theory**

by

**Yuen-Kwok Chan**-

**arXiv.org**

The author provides a systematic, thorough treatment of the foundations of probability theory and stochastic processes along the lines of E. Bishop's constructive analysis. Every existence result presented shall be a construction ...

(

**1746**views)

**Probability on Trees and Networks**

by

**Russell Lyons, Yuval Peres**-

**Cambridge University Press**

This book is concerned with certain aspects of discrete probability on infinite graphs that are currently in vigorous development. Of course, finite graphs are analyzed as well, but usually with the aim of understanding infinite graphs and networks.

(

**2323**views)