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Probability Models (04 Edition)

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Synopses & Reviews

Please note that used books may not include additional media (study guides, CDs, DVDs, solutions manuals, etc.) as described in the publisher comments.

Publisher Comments:

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.

Synopsis:

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.

Synopsis:

Includes bibliographical references (p. 227-228) and index.

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.

Product Details

ISBN:
9781852334314
Author:
Haigh, John
Publisher:
Springer
Author:
Haigh, J.
Author:
Haigh, John, Dr
Location:
London
Subject:
Probabilities
Subject:
Probabilitâes
Subject:
Probability & Statistics - General
Subject:
Statistics
Subject:
First Year
Subject:
Probability
Subject:
Probability Theory.
Subject:
SUMS
Subject:
undergrate textbook
Subject:
Probability Theory and Stochastic Processes
Subject:
Mathematics | Probability and Statistics
Subject:
Mathematics
Subject:
Language, literature and biography
Subject:
mathematics and statistics
Subject:
Distribution (Probability theory)
Copyright:
Edition Description:
2002. Corr. 2nd
Series:
Springer undergraduate mathematics series
Series Volume:
2001-03
Publication Date:
20040924
Binding:
TRADE PAPER
Language:
English
Illustrations:
Y
Pages:
264
Dimensions:
235 x 178 mm 470 gr

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Probability Models (04 Edition) Used Trade Paper
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$38.00 In Stock
Product details 264 pages Springer-Verlag - English 9781852334314 Reviews:
"Synopsis" by , 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.
"Synopsis" by , Includes bibliographical references (p. 227-228) and index.
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