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Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, *Fundamental Probability* provides an engaging and hands-on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools.

Based on international teaching experience with students of statistics, mathematics, finance and econometrics, the book:

- Presents new, innovative material alongside the classic theory.
- Goes beyond standard presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate sampling schemes, fat-tailed distributions, and several basic concepts used in finance.
- Emphasises computational matters and programming methods via generous use of examples in MATLAB.
- Includes a large, self-contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz’ rule, exchange of derivative and integral, Fubini’s theorem, and univariate and multivariate Taylor series.
- Presents over 150 end-of-chapter exercises, graded in terms of their difficulty, and accompanied by a full set of solutions online.

This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer science who possess the prerequisite knowledge of basic calculus and linear algebra.

*"synopsis" may belong to another edition of this title.*

Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, *Fundamental Probability: A Computational Approach* provides an engaging and hands-on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools.

Based on international teaching experience with students of statistics, mathematics, finance and econometrics, the book:

- Presents new, innovative material alongside the classic theory.
- Goes beyond standard presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate sampling schemes, fat-tailed distributions, and several basic concepts used in finance.
- Emphasises computational matters and programming methods via generous use of examples in MATLAB.
- Includes a large, self-contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz’ rule, exchange of derivative and integral, Fubini’s theorem, and univariate and multivariate Taylor series.
- Presents over 150 end-of-chapter exercises, graded in terms of their difficulty, and accompanied by a full set of solutions online.

This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer science who possess the prerequisite knowledge of basic calculus and linear algebra.

**Marc S Paolella**, Swiss Banking Institute, University of Zurich, Switzerland

*"About this title" may belong to another edition of this title.*

Published by
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(2006)

ISBN 10: 0470025948
ISBN 13: 9780470025949

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**Book Description **Wiley, 2006. Hardcover. Book Condition: New. book. Bookseller Inventory # 0470025948

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Published by
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(2006)

ISBN 10: 0470025948
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**Book Description **Wiley, 2006. Book Condition: New. Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Preface.A note to the student (and instructor).A note to the instructor (and student).Acknowledgements.Introduction.PART I: BASIC PROBABILITY.1. Combinatorics.1.1 Basic counting.1.2 Generalized binomial coefficients.1.3 Combinatoric identities and the use of induction.1.4 The binomial and multinomial theorems.1.4.1 The binomial theorem.1.4.2 An extension of the binomial theorem.1.4.3 The multinomial theorem.1.5 The gamma and beta functions.1.5.1 The gamma function.1.5.2 The beta function.1.6 Problems.2. Probability spaces and counting.2.1 Introducing counting and occupancy problems.2.2 Probability spaces.2.2.1 Introduction.2.2.2 Definitions.2.3 Properties.2.3.1 Basic properties.2.3.2 Advanced properties.2.3.3 A theoretical property.2.4 Problems.3. Symmetric spaces and conditioning.3.1 Applications with symmetric probability spaces.3.2 Conditional probability and independence.3.2.1 Total probability and Bayes' rule.3.2.2 Extending the law of total probability.3.2.3 Statistical paradoxes and fallacies.3.3 The problem of the points.3.3.1 Three solutions.3.3.2 Further gambling problems.3.3.3 Some historical references.3.4 Problems.PART II: DISCRETE RANDOM VARIABLES.4. Univariate random variables.4.1 Definitions and properties.4.1.1 Basic definitions and properties.4.1.2 Further definitions and properties.4.2 Discrete sampling schemes.4.2.1 Bernoulli and binomial.4.2.2 Hypergeometric.4.2.3 Geometric and negative binomial.4.2.4 Inverse hypergeometric.4.2.5 Poisson approximations.4.2.6 Occupancy distributions.4.3 Transformations.4.4 Moments.4.4.1 Expected value of X.4.4.2 Higher-order moments.4.4.3 Jensen's inequality.4.5 Poisson processes.4.6 Problems.5. Multivariate random variables.5.1 Multivariate density and distribution.5.1.1 Joint cumulative distribution functions.5.1.2 Joint probability mass and density functions.5.2 Fundamental properties of multivariate random variables.5.2.1 Marginal distributions.5.2.2 Independence.5.2.3 Exchangeability.5.2.4 Transformations.5.2.5 Moments.5.3 Discrete sampling schemes.5.3.1 Multinomial.5.3.2 Multivariate hypergeometric.5.3.3 Multivariate negative binomial.5.3.4 Multivariate inverse hypergeometric.5.4 Problems.6. Sums of random variables.6.1 Mean and variance.6.2 Use of exchangeable Bernoulli random variables.6.2.1 Examples with birthdays.6.3 Runs distributions.6.4 Random variable decomposition.6.4.1 Binomial, negative binomial and Poisson.6.4.2 Hypergeometric.6.4.3 Inverse hypergeometric.6.5 General linear combination of two random variables.6.6 Problems.PART III: CONTINUOUS RANDOM VARIABLES.7. Continuous univariate random variables.7.1 Most prominent distributions.7.2 Other popular distributions.7.3 Univariate transformations.7.3.1 Examples of one-to-one transformatio. Bookseller Inventory # ABE_book_new_0470025948

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Published by
Somerset, New Jersey, U.S.A.: John Wiley & Sons Inc
(2006)

ISBN 10: 0470025948
ISBN 13: 9780470025949

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**Book Description **Somerset, New Jersey, U.S.A.: John Wiley & Sons Inc, 2006. Hardcover. Book Condition: New. Ship out 1 business day,Brand new,US edition, Free tracking number usually 2-4 biz days delivery to worldwide Same shipping fee with US, Canada,Europe country, Australia, item will ship out from either LA or Asia,k. Bookseller Inventory # ABE-6274595567

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John Wiley and Sons Ltd, United Kingdom
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**Book Description **John Wiley and Sons Ltd, United Kingdom, 2006. Hardback. Book Condition: New. 248 x 174 mm. Language: English Brand New Book. Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, Fundamental Probability provides an engaging and hands on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools.Based on international teaching experience with students of statistics, mathematics, finance and econometrics, the book presents new, innovative material alongside the classic theory. It goes beyond standard presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate sampling schemes, fat tailed distributions, and several basic concepts used in finance. It emphasises computational matters and programming methods via generous use of examples in MATLAB. It includes a large, self contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz rule, exchange of derivative and integral, Fubini s theorem, and univariate and multivariate Taylor series. It presents over 150 end of chapter exercises, graded in terms of their difficulty, and accompanied by a full set of solutions online.This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer science who possess the prerequisite knowledge of basic calculus and linear algebra. Bookseller Inventory # AAH9780470025949

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Published by
John Wiley and Sons Ltd, United Kingdom
(2006)

ISBN 10: 0470025948
ISBN 13: 9780470025949

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**Book Description **John Wiley and Sons Ltd, United Kingdom, 2006. Hardback. Book Condition: New. 248 x 174 mm. Language: English Brand New Book. Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, Fundamental Probability provides an engaging and hands on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools.Based on international teaching experience with students of statistics, mathematics, finance and econometrics, the book presents new, innovative material alongside the classic theory. It goes beyond standard presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate sampling schemes, fat tailed distributions, and several basic concepts used in finance. It emphasises computational matters and programming methods via generous use of examples in MATLAB. It includes a large, self contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz rule, exchange of derivative and integral, Fubini s theorem, and univariate and multivariate Taylor series. It presents over 150 end of chapter exercises, graded in terms of their difficulty, and accompanied by a full set of solutions online.This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer science who possess the prerequisite knowledge of basic calculus and linear algebra. Bookseller Inventory # AAH9780470025949

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ISBN 10: 0470025948
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**Book Description **Wiley?Blackwell, 2006. HRD. Book Condition: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Bookseller Inventory # FW-9780470025949

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**Book Description **John Wiley and Sons Ltd. Hardback. Book Condition: new. BRAND NEW, Fundamental Probability: A Computational Approach, Marc Paolella, Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, "Fundamental Probability" provides an engaging and hands on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools.Based on international teaching experience with students of statistics, mathematics, finance and econometrics, the book presents new, innovative material alongside the classic theory. It goes beyond standard presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate sampling schemes, fat tailed distributions, and several basic concepts used in finance. It emphasises computational matters and programming methods via generous use of examples in MATLAB. It includes a large, self contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz' rule, exchange of derivative and integral, Fubini's theorem, and univariate and multivariate Taylor series. It presents over 150 end of chapter exercises, graded in terms of their difficulty, and accompanied by a full set of solutions online.This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer science who possess the prerequisite knowledge of basic calculus and linear algebra. Bookseller Inventory # B9780470025949

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**Book Description **Wiley?Blackwell, 2006. HRD. Book Condition: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bookseller Inventory # IP-9780470025949

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**Book Description **2006. Hardcover. Book Condition: New. 1st. 174mm x 34mm x 252mm. Hardcover. Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, "Fundamenta.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 466 pages. 1.052. Bookseller Inventory # 9780470025949

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Published by
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**Book Description **Wiley, 2006. Hardcover. Book Condition: New. Bookseller Inventory # INGM9780470025949

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