An Introduction to Probability Theory and Its Applications

  title={An Introduction to Probability Theory and Its Applications},
  author={William Feller},
  • W. Feller
  • Published 1 September 1951
  • Mathematics
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Fundamentals of Probability

The first chapter is devoted to a fast but rigorous introduction to the basic concepts and results of probability theory, which are required as a support to readers who may not be familiar with them.

Review of Probability Theory

This chapter provides a self-contained review of the foundations of probability theory, in order to fix notations and introduce mathematical objects employed in the remaining chapters. In particular

Tutorial on large deviations for the binomial distribution.

Probability: Theory and Examples

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

Probabilities of Competing Binomial Random Variables

Asymptotic and monotonicity/convexity properties for this competing probability as a function of $n$ are obtained, and surprising phase transition phenomenons as parameters d, r and $\alpha$ vary are demonstrated.

Useful Definitions and Facts of Probability Theory for Further Reading

In Chap. 10 are presented supplementary facts of probability theory which can be useful in studying error analysis problems. Sections of this chapter contain information on statistical linearization,

An introduction to probability theory

Basic Concepts of Probability Theory

This part is an introduction to standard concepts of probability theory. We discuss a variety of exercises on moment and dependence calculations with a real market example. We also study the

Discrete problems in probability theory

A short survey is given of some directions in probability theory that have developed most intensively in recent years. Separable statistics and criteria for the verification of statistical hypotheses