Synopses & Reviews
This text provides undergraduate mathematics students with an introduction to the modern theory of probability as well as the roots of the theory's mathematical ideas and techniques. Centered around the concept of measure and integration, the treatment is applicable to other branches of analysis and explores more specialized topics, including convergence theorems and random sequences and functions.
The initial part is devoted to an exploration of measure and integration from first principles, including sets and set functions, general theory, and integrals of functions of real variables. These topics provide tools for use in the second part, which emphasizes underlying mathematical ideas, including the roles of random variables and limit processes in probability. The concise format and exposition offer an ideal review of the subject for students with some background in probability.
Synopsis
Introductory treatment develops the theory of integration in a general context, making it applicable to other branches of analysis. More specialized topics include convergence theorems and random sequences and functions. 1963 edition.
Synopsis
This text provides undergraduate mathematics students with an introduction to the modern theory of probability as well as the roots of the theory's mathematical ideas and techniques. Centered around the concept of measure and integration, the work is applicable to other branches of analysis and explores more specialized topics, including convergence theorems and random sequences and functions. 1963 edition.
Table of Contents
Preface Part 1 1. Sets and Set-Functions 2. General Theory of Integration and Measure 3. Integrals of Functions of Real Variables Part 2 4. Randon Variables and Probability 5. Limit Processes in Probability Index