Probability Models

John Haigh

256 pages, parution le 27/02/2002

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Résumé

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 analyse 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.

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.

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	John Haigh
Parution	27/02/2002
Nb. de pages	256
Format	17 x 23,5
Couverture	Broché
Poids	440g
Intérieur	Noir et Blanc
EAN13	9781852334314
ISBN13	978-1-85233-431-4