Probability Models / Edition 1

Probability Models / Edition 1

by John Haigh, J. Haigh
     
 

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ISBN-10: 1852334312

ISBN-13: 9781852334314

Pub. Date: 09/24/2004

Publisher: Springer London

Probability Models is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics. It describes how to set up and analyze models of real-life phenomena that involve elements of chance. Motivation comes from everyday experiences of probability via dice and cards, the idea of fairness in games of chance,

Overview

Probability Models is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics. It describes how to set up and analyze models of real-life phenomena that involve elements of chance. Motivation comes from everyday experiences of probability via dice and cards, the idea of fairness in games of chance, and the random ways in which, say, birthdays are shared or particular events arise. Applications include branching processes, random walks, Markov chains, queues, renewal theory, and Brownian motion. No specific knowledge of the subject is assumed, only a familiarity with the notions of calculus, and the summation of series. Where the full story would call for a deeper mathematical background, the difficulties are noted and appropriate references given. The main topics arise naturally, with definitions and theorems supported by fully worked examples and some 200 set exercises, all with solutions.

Product Details

ISBN-13:
9781852334314
Publisher:
Springer London
Publication date:
09/24/2004
Series:
Springer Undergraduate Mathematics Series
Edition description:
1st ed. 2002. Corr. 2nd printing 2004
Pages:
256
Product dimensions:
6.84(w) x 9.28(h) x 0.64(d)

Related Subjects

Table of Contents

Preface.- Probability Spaces.- Conditional Probability and Independence.- Common Probability Distributions.- Random Variables.-Sums of Random Variables.- Convergence and Limit Theorems.- Stochastic Processes in Discrete Time.- Stochastic Processes in Continuous Time.- Appendix: Common Distributions, Mathfacts.- Bibliography.- Solutions.- Index.

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