Probability Theory Overview

Probability theory is a branch of mathematics that concerned with the analysis of random phenomena. The outcome of a random event cannot be determined before it occurs, but it may be any one of several possible outcomes. The actual outcome is considered to be determined by chance.

The word probability has several meanings in ordinary conversation. Two of these are particularly important for the development and applications of the mathematical theory of probability. This culminated in modern probability theory, on foundations laid by Andrey Nikolaevich Kolmogorov.

Kolmogorov combined the notion of sample space, introduced by Richard von Mises, and measure theory and presented his axiom system for probability theory in 1933. Fairly quickly this became the mostly undisputed axiomatic basis for modern probability theory but alternatives exist, in particular the adoption of finite rather than countable additivity by Bruno de Finetti.

Particular emphasis is placed upon stopping times, both as tools in proving theorems and as objects of interest themselves. The book covers a comprehensive course in probability for the students of economics, statistics and the physical sciences.

It presents a thorough treatment of probability ideas and techniques necessary for a firm understanding of the subject and has been designed in such a way that a previous acquaintance with mathematics and statistics is not necessary.