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A first course in probability and Ma...
~
Modica, Giuseppe.
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A first course in probability and Markov chains
Record Type:
Electronic resources : Monograph/item
Title/Author:
A first course in probability and Markov chains/ Giuseppe Modica and Laura Poggiolini.
Author:
Modica, Giuseppe.
other author:
Poggiolini, Laura.
Published:
Chichester, West Sussex :John Wiley & Sons Ltd., : 2013.,
Description:
1 online resource (xii, 334 p.)
Subject:
Markov processes. -
Online resource:
http://onlinelibrary.wiley.com/book/10.1002/9781118477793
ISBN:
9781118477793 (electronic bk.)
A first course in probability and Markov chains
Modica, Giuseppe.
A first course in probability and Markov chains
[electronic resource] /Giuseppe Modica and Laura Poggiolini. - Chichester, West Sussex :John Wiley & Sons Ltd.,2013. - 1 online resource (xii, 334 p.)
Includes bibliographical references and index.
"Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra"--
ISBN: 9781118477793 (electronic bk.)
LCCN: 2012042679Subjects--Topical Terms:
532104
Markov processes.
Index Terms--Genre/Form:
542853
Electronic books.
LC Class. No.: QA274.7 / .M63 2013
Dewey Class. No.: 519.2/33
A first course in probability and Markov chains
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A first course in probability and Markov chains
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[electronic resource] /
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Giuseppe Modica and Laura Poggiolini.
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Chichester, West Sussex :
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John Wiley & Sons Ltd.,
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2013.
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1 online resource (xii, 334 p.)
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Includes bibliographical references and index.
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"Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra"--
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Provided by publisher.
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"A first course in Probability and Markov Chains presents an introduction to the basic elements in statistics and focuses in two main areas"--
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588
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Description based on online resource; title from digital title page (viewed February 11, 2013).
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http://onlinelibrary.wiley.com/book/10.1002/9781118477793
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EB QA274.7 .M63 2013
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