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ISBN: 9780521899048

[ED: Hardcover], [PU: CAMBRIDGE UNIV PR], Update of this popular introduction to probability theory and information theory with new material on Markov chains. This updated textbook is an excellent way to introduce probability and information theory to new students in mathematics, computer science, engineering, statistics, economics, or business studies. Only requiring knowledge of basic calculus, it starts by building a clear and systematic foundation to the subject: the concept of probability is given particular attention via a simplified discussion of measures on Boolean algebras. The theoretical ideas are then applied to practical areas such as statistical inference, random walks, statistical mechanics and communications modelling. Topics covered include discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem and the coding and transmission of information, and added for this new edition is material on Markov chains and their entropy. Lots of examples and exercises are included to illustrate how to use the theory in a wide range of applications, with detailed solutions to most exercises available online for instructors. Review quote: Reviews for the first edition: 'I found the book interesting and entertaining ... The level of difficulty of the material is well judged ...' D. A. Stephens, The Statistician 'This text provides a blend of the traditional disciplines of probability theory and the relatively new field of information science in a well written manner ... the author succeeds in introducing concepts of probability theory gently paced and user friendly as stated on page xi of the preface ... The blend of probability theory and information science makes this an innovative text... The innovative blend of probability theory and information theory make this text a good choice for teachers wanting to present both a traditional background and modern ideas to their students.' Journal of the American Statistical Association 'Reviewing this book was a pleasure. Clearly the author is delighted by his subject and this attitude is communicated well ... this is an excellent book which will make a stimulating text for Honours courses in probability for applied mathematicians, statisticians, physicists or engineers' John M. Halley, The Statistician Table of contents: Preface to the first edition Preface to the second edition 1. Introduction 2. Combinatorics 3. Sets and measures 4. Probability 5. Discrete random variables 6. Information and entropy 7. Communication 8. Random variables with probability density functions 9. Random vectors 10. Markov chains and their entropy Exploring further Appendix 1. Proof by mathematical induction Appendix 2. Lagrange multipliers Appendix 3. Integration of exp (-x) Appendix 4. Table of probabilities associated with the standard normal distribution Appendix 5. A rapid review of Matrix algebra Selected solutions Index. 250 p., 65 line fig. 3 tab. 240 exercises 105 worked examples - 252 x 177 mm Versandfertig in über 4 Wochen, [SC: 0.00], Neuware, gewerbliches Angebot

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ISBN: 9780521899048

[ED: Hardcover], [PU: CAMBRIDGE UNIV PR], Update of this popular introduction to probability theory and information theory with new material on Markov chains. This updated textbook is an excellent way to introduce probability and information theory to new students in mathematics, computer science, engineering, statistics, economics, or business studies. Only requiring knowledge of basic calculus, it starts by building a clear and systematic foundation to the subject: the concept of probability is given particular attention via a simplified discussion of measures on Boolean algebras. The theoretical ideas are then applied to practical areas such as statistical inference, random walks, statistical mechanics and communications modelling. Topics covered include discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem and the coding and transmission of information, and added for this new edition is material on Markov chains and their entropy. Lots of examples and exercises are included to illustrate how to use the theory in a wide range of applications, with detailed solutions to most exercises available online for instructors. Review quote: Reviews for the first edition: 'I found the book interesting and entertaining ... The level of difficulty of the material is well judged ...' D. A. Stephens, The Statistician 'This text provides a blend of the traditional disciplines of probability theory and the relatively new field of information science in a well written manner ... the author succeeds in introducing concepts of probability theory gently paced and user friendly as stated on page xi of the preface ... The blend of probability theory and information science makes this an innovative text... The innovative blend of probability theory and information theory make this text a good choice for teachers wanting to present both a traditional background and modern ideas to their students.' Journal of the American Statistical Association 'Reviewing this book was a pleasure. Clearly the author is delighted by his subject and this attitude is communicated well ... this is an excellent book which will make a stimulating text for Honours courses in probability for applied mathematicians, statisticians, physicists or engineers' John M. Halley, The Statistician Table of contents: Preface to the first edition Preface to the second edition 1. Introduction 2. Combinatorics 3. Sets and measures 4. Probability 5. Discrete random variables 6. Information and entropy 7. Communication 8. Random variables with probability density functions 9. Random vectors 10. Markov chains and their entropy Exploring further Appendix 1. Proof by mathematical induction Appendix 2. Lagrange multipliers Appendix 3. Integration of exp (-x) Appendix 4. Table of probabilities associated with the standard normal distribution Appendix 5. A rapid review of Matrix algebra Selected solutions Index. 250 p., 65 line fig. 3 tab. 240 exercises 105 worked examples - 252 x 177 mm Versandfertig in 2-4 Wochen, [SC: 0.00], Neuware, gewerbliches Angebot

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ISBN: 9780521899048

ID: 978052189904

This new and updated textbook is an excellent way to introduce probability and information theory to students new to mathematics, computer science, engineering, statistics, economics, or business studies. Only requiring knowledge of basic calculus, it begins by building a clear and systematic foundation to probability and information. Classic topics covered include discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem and the coding and transmission of information. Newly covered for this edition is modern material on Markov chains and their entropy. Examples and exercises are included to illustrate how to use the theory in a wide range of applications, with detailed solutions to most exercises available online for instructors. David Applebaum, Books, Science and Nature, Probability and Information: An Integrated Approach Books>Science and Nature, Cambridge University Press

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ISBN: 9780521899048

ID: 352946

Update of this popular introduction to probability theory and information theory with new material on Markov chains. Language Arts & Disciplines Language Arts & Disciplines eBook, Cambridge University Press

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2008, ISBN: 9780521899048

ID: 8772443

[ED: 2], 2nd Revised edition, Hardcover, Buch, [PU: Cambridge University Press]

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Title: | ## Probability and Information: An Integrated Approach |

ISBN: |

** Details of the book - Probability and Information: An Integrated Approach**

EAN (ISBN-13): 9780521899048

ISBN (ISBN-10): 0521899044

Hardcover

Publishing year: 2008

Publisher: CAMBRIDGE UNIV PR

273 Pages

Weight: 0,720 kg

Language: eng/Englisch

Book in our database since 15.06.2008 09:45:42

Book found last time on 22.04.2017 20:47:23

ISBN/EAN: 0521899044

ISBN - alternate spelling:

0-521-89904-4, 978-0-521-89904-8

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