Billingsley P. Convergence of Probability Measures

Richard F. Bass, 2001. - 47 pages. Basic notions. Independence. Convergence. Weak law of large numbers Techniques related to almost sure convergence. Strong law of large numbers. Uniform integrability. Complements to the SLLN. Conditional expectation. Stopping times. Optional stopping. Doob’s inequalities. Martingale convergence theorems. Applications of martingales. Weak convergence. Characteristic functions. Inversion formula. Continuity theor...

Lecture Notes in Mathematics 1717. Springer, 2000. - 289 pages. Introduces the basic notions and properties of subordinators, such as the Levy-Khintchine formula, Itos decomposition, renewal measures, and ranges.

Cambridge University Press, 2005, Pages: 393. This text is designed both for students of probability and stochastic processes and for students of functional analysis. For the reader not familiar with functional analysis a detailed introduction to necessary notions and facts is provided. However, this is not a straight textbook in functional analysis; rather, it presents some chosen parts of functional analysis that help understand ideas from prob...

Distribution function. Measure theory. Random variable. Expectation. Independence. Convergence concepts. Law of large numbers. Random series.

Cambridge University Press, 2009. - 254 pages. This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probab...

John Wiley & Sons, 1963. - 695 pages. Probability theory can be understood as a mathematical model for the intuitive notion of uncertainty. Without probability theory all the stochastic models in Physics, Biology, and Economics would either not have been developed or would not be rigorous. Also, probability is used in many branches of pure mathematics, even in branches one does not expect this, like in convex geometry.

(Математическая статистика - Chapman & Hall/CRC, 2000). This book is intended as a textbook (or reference) for a full year Master’s level (or senior level undergraduate) course in mathematical statistics aimed at students in statistics, biostatistics, and related fields. Contents: Introduction to Probability. Random experiments. Probability measures. Conditional probability and independence. Random variables. Transformations of random variab...

McGraw-Hill, 1998, 376 pages. The purpose of this book is to present a modern introduction to probability and statistics using background of calculus. For convenience the book is divided into two parts. The first deals with probability (and by itself can be used to provide an introduction to the subject), while the second deals with statistics. The book is designed to be used either as a textbook for formal course in probability and statistics or...

Wiley-Interscience, 608 pages, 1995. Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probabilit...

For Dummies, 2006. - 384 pages. Packed with practical tips and techniques for solving probability problems Increase your chances of acing that probability exam -- or winning at the casino! Whether you're hitting the books for a probability or statistics course or hitting the tables at a casino, working out probabilities can be problematic. This book helps you even the odds. Using easy-to-understand explanations and examples, it demystifies pro...