Probability: elements of the mathematical theory

By C.R. Heathcote

Book Overview

Designed for students studying mathematical statistics and probability after completing a course in calculus and real variables, this text deals with basic notions of probability spaces, random... This description may be from another edition of this product.

• Format: Hardcover
• Language: English
• ISBN: 0045190054
• ISBN13: 9780045190058
• Release Date: January 1971
• Publisher: Wiley
• Length: 267 Pages
• Weight: 1.05 lbs.

Customer Reviews

a quick introduction

This book is for students and readers with some mathematical background, but not much. It offers a quick introduction to the fundamental concepts and tools of probability. It doesn't cover many applications, but that is covered instead in other books; some of which are also in the Dover series. Practical uses of probability include: Testing of data set, sampling, insurance topics, quality checking, finance, investment, and finance, to mention only a few. Heathcote's book is not intimidating; just 265 pages. It has exercises, useful in the classroom or in self-study. They are well chosen and help the novice assimilating the theory and turning practical problems into numbers. It begins with events, probability space, combination of events using the mathematical notions of union and intersection, sigma algebras, random variables; then it turns to tools from analysis, Bayes' theorem, distributions, convergence theorems. The book offers a quick entry into computations with probability, and it concludes with the law(s) of large numbers, and Markov chains. It is a nice supplement to for example Rozanov's little book Probability Theory, also in the Dover series. Review by Palle Jorgensen, August 2008.

Concise introduction to the mathematical theory of probabili

Heathcote is a nice little introduction to mathematical probability theory. It is an introduction in the sense that it does not assume familiarity with probability theory. It develops the subject without relying on measure theory or Lebesgue integration, topics which are perhaps too advanced for an introductory text. For more advanced treatments consult, for example, Shiryaev. The notation and typesetting is clear and clean throughout. Applied examples are scarse, with applications being reserved mainly for the problem sets. Overall this is a good book for the student interested in learning some of the deeper mathematics underlying probability.