An Introduction to Probability and Random Processes
by Gian-Carlo Rota, Kenneth Baclawski
Number of pages: 467
The purpose of this course is to learn to think probabilistically. We begin by giving a bird's-eye view of probability by examining some of the great unsolved problems of probability theory. It's only by seeing what the unsolved problems are that one gets a feeling for a field.
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by Pawel J. Szablowski - arXiv
We formulate conditions for convergence of Laws of Large Numbers and show its links with of parts mathematical analysis such as summation theory, convergence of orthogonal series. We present also various applications of Law of Large Numbers.
by Rick Durrett - Cambridge University Press
An introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It concentrates on the results that are the most useful for applications.
by David Nualart - The University of Kansas
From the table of contents: Stochastic Processes (Probability Spaces and Random Variables, Definitions and Examples); Jump Processes (The Poisson Process, Superposition of Poisson Processes); Markov Chains; Martingales; Stochastic Calculus.
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.