Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.
This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design.
The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.
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"This small (less than 200 pages) but much-needed book contains a wealth of worked-out numerical examples of Bayesian treatments of data, expounded from a theoretical standpoint identical to ours. It should be considered an adjunct to the present work, supplying a great deal of practical advice for the beginner, at an elementary level that will be grasped readily by every science or engineering student."--Ed Jaynes in 'Probability Theory: The Logic of Science', CUP 2003
Devinderjit Singh Sivia
Rutherford Appleton Laboratory
Chilton
Oxon
OX11 5DJ John Skilling
Maximum Entropy Data Consultants
42 Southgate Street
Bury St Edmonds
Suffolk
IP33 2AZ
"Review from previous edition Providing a clear rationale for some of the most widely used procedures."--European Journal of Engineering Education
"This small (less than 200 pages) but much-needed book contains a wealth of worked-out numerical examples of Bayesian treatments of data, expounded from a theoretical standpoint identical to ours. It should be considered an adjunct to the present work, supplying a great deal of practical advice for the beginner, at an elementary level that will be grasped readily by every science or engineering student."--Ed Jaynes in 'Probability Theory: The Logic of Science', CUP 2003
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1. Data Analysis
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OUP Oxford 2006-06-01, Oxford
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ISBN 10: 0198568320
ISBN 13: 9780198568322
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Descripción OUP Oxford 2006-06-01, Oxford, 2006. paperback. Estado de conservación: New. Nº de ref. de la librería 9780198568322
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2. Data Analysis: A Bayesian Tutorial (Paperback)
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Oxford University Press, United Kingdom
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Descripción Oxford University Press, United Kingdom, 2006. Paperback. Estado de conservación: New. 2nd Revised edition. Language: English . Brand New Book. Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis. This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design. The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called nested sampling . Features * An easy to read tutorial introduction to data anlaysis. * Concise, being one of the slimmest books in the field! * Self-contained--assumes little or no previous statistical training. * Good illustrative examples where the basic concepts are explained with a series of examples that become progressively more advanced, but that are always kept as simple as possible to aid understanding. * A contribution from John Skilling, an expert in numerical techniques. He introduces the simple but powerful new nested sampling technique for Bayesian computiaton. Nº de ref. de la librería AAU9780198568322
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3. Data Analysis: A Bayesian Tutorial (Paperback)
Editorial:
Oxford University Press, United Kingdom
(2006)
ISBN 10: 0198568320
ISBN 13: 9780198568322
Nuevos
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Cantidad: 10
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Descripción Oxford University Press, United Kingdom, 2006. Paperback. Estado de conservación: New. 2nd Revised edition. Language: English . Brand New Book. Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis. This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design. The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called nested sampling . Features * An easy to read tutorial introduction to data anlaysis. * Concise, being one of the slimmest books in the field! * Self-contained--assumes little or no previous statistical training. * Good illustrative examples where the basic concepts are explained with a series of examples that become progressively more advanced, but that are always kept as simple as possible to aid understanding. * A contribution from John Skilling, an expert in numerical techniques. He introduces the simple but powerful new nested sampling technique for Bayesian computiaton. Nº de ref. de la librería AAU9780198568322
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4. Data Analysis: A Bayesian Tutorial Format: Paperback
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Descripción Oxford University Press. Estado de conservación: New. Brand New. Nº de ref. de la librería 0198568320
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5. Data Analysis: A Bayesian Tutorial (2nd Revised edition)
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Oxford University Press
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Descripción Oxford University Press. Paperback. Estado de conservación: new. BRAND NEW, Data Analysis: A Bayesian Tutorial (2nd Revised edition), Devinderjit Sivia, John Skilling, Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis. This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design. The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'. Features * An easy to read tutorial introduction to data anlaysis. * Concise, being one of the slimmest books in the field! * Self-contained--assumes little or no previous statistical training. * Good illustrative examples where the basic concepts are explained with a series of examples that become progressively more advanced, but that are always kept as simple as possible to aid understanding. * A contribution from John Skilling, an expert in numerical techniques. He introduces the simple but powerful new 'nested sampling' technique for Bayesian computiaton. Nº de ref. de la librería B9780198568322
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6. Data Analysis
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Oxford University Press
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Descripción Oxford University Press, 2006. Estado de conservación: New. 2006. 2nd Edition. Paperback. Num Pages: 264 pages, 68 line drawings + 1 halftone. BIC Classification: PBT; PHS. Category: (P) Professional & Vocational. Dimension: 232 x 157 x 16. Weight in Grams: 416. . . . . . . Nº de ref. de la librería V9780198568322
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7. Data Analysis: A Bayesian Tutorial
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Descripción Estado de conservación: New. Depending on your location, this item may ship from the US or UK. Nº de ref. de la librería 97801985683220000000
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8. Data Analysis
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Descripción OUP Oxford, 2006. PAP. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería FU-9780198568322
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9. Data Analysis: A Bayesian Tutorial
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Descripción Oxford University Press, U.S.A., 2006. Estado de conservación: New. book. Nº de ref. de la librería ria9780198568322_rkm
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10. Data Analysis
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Descripción Oxford University Press. Estado de conservación: New. 2006. 2nd Edition. Paperback. Num Pages: 264 pages, 68 line drawings + 1 halftone. BIC Classification: PBT; PHS. Category: (P) Professional & Vocational. Dimension: 232 x 157 x 16. Weight in Grams: 416. . . . . . Books ship from the US and Ireland. Nº de ref. de la librería V9780198568322
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