Probability: Theory and Examples
by Rick Durrett
Publisher: Cambridge University Press 2010
Number of pages: 372
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.
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by Curtis T. McMullen - Harvard University
Contents: The Sample Space; Elements of Combinatorial Analysis; Random Walks; Combinations of Events; Conditional Probability; The Binomial and Poisson Distributions; Normal Approximation; Unlimited Sequences of Bernoulli Trials; etc.
by Pierre Simon Laplace - Chapman & Hall
Classic book on probability theory. It demonstrates, without the use of higher mathematics, the application of probability to games of chance, physics, reliability of witnesses, astronomy, insurance, democratic government, and many other areas.
by Cosma Rohilla Shalizi - Carnegie Mellon University
Text for a second course in stochastic processes. It is assumed that you have had a first course on stochastic processes, using elementary probability theory. You will study stochastic processes within the framework of measure-theoretic probability.
by C. M. Grinstead, J. L. Snell - American Mathematical Society
The textbook for an introductory course in probability for students of mathematics, physics, engineering, social sciences, and computer science. It presents a thorough treatment of techniques necessary for a good understanding of the subject.