Chung K.L. A Course In Probability Theory

Springer, 2007. - 218 pages. Introductory Probability is a pleasure to read and provides a fine answer to the question: How do you construct Brownian motion from scratch, given that you are a competent analyst? There are at least two ways to develop probability theory. The more familiar path is to treat it as its own discipline, and work from intuitive examples such as coin flips and conundrums such as the Monty Hall problem. An alternative is...

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.

This classic book is intended to be the first introduction to probability and statistics written with an emphasis on the analytic approach to the problems discussed. Topics include the axiomatic setup of probability theory, polynomial distribution, finite Markov chains, distribution functions and convolution, the laws of large numbers (weak and strong), characteristic functions, the central limit theorem, infinitely divisible distributions, and M...

Springer, 2009. - 340 pages. This book presents elementary probability theory with interesting and well-chosen applications that illustrate the theory. An introductory chapter reviews the basic elements of differential calculus which are used in the material to follow. The theory is presented systematically, beginning with the main results in elementary probability theory. This is followed by material on random variables. Random vectors, includi...

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, edition 2010. - 267 pages. This book is intended as a popular, but abbreviated treatise on probability theory. Basic concepts and techniques are introduced and illustrated mainly by drawing from a wealth of entertaining, paradoxical, and mind-boggling probability problems (such as the birthday problem or the Monty Hall problem). The writing style is purposefully enjoyable and mostly non-technical. The pace is leisurely. No knowledge of ca...

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...

Prentice Hall, 2009. - 552 pages. 8th Edition A First Course in Probability, Eighth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary cal...

Book 2007, 782p, ISBN-13: 978-0-12-598062-3 Ninth Edition content Introduction to Probability Theory Introduction to Probability Theory Conditional Probability and Conditional Expectation Markov Chains The Exponential Distribution and the Poisson Process Continuous-Time Markov Chains Renewal Theory and Its Applications Queueing Theory Reliability Theory Brownian Motion and Stationary Processes Simulation Appendix: Solutions to Starred Exercises