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 Leif Mejlbro - BookBoon
Contents: Some theoretical background; Exponential Distribution; The Normal Distribution; Central Limit Theorem; Maxwell distribution; Gamma distribution; Normal distribution and Gamma distribution; Convergence in distribution; 2 distribution; etc.
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.
by Michael Roeckner - Universitaet Bielefeld
From the table of contents: Introduction to Pathwise Ito-Calculus; (Semi-)Martingales and Stochastic Integration; Markov Processes and Semigroups - Application to Brownian Motion; Girsanov Transformation; Time Transformation.
by I. Todhunter - Kessinger Publishing, LLC
History of the probability theory from the time of Pascal to that of Laplace (1865). Todhunter gave a close account of the difficulties involved and the solutions offered by each investigator. His studies were thorough and fully documented.