9780198568322 - Data Analysis: A Bayesian Tutorial [Lingua inglese] di SIVIA, Devinderjit (32 risultati)

Paperback. Condizione: Fair. A readable copy of the book which may include some defects such as highlighting and notes. Cover and pages may be creased and show discolouration.

Paperback. Condizione: Fair. 2. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

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Paperback. Condizione: Good. 2nd Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Condizione: New.

Paperback. Condizione: New. 2nd. 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'.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In.

Condizione: NEW.

Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: new. New Copy. Customer Service Guaranteed.

Paperback. Condizione: new. Paperback. 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 illustratedwith a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximumlikelihood, 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'. This is the second edition of the first tutorial book on Bayesian methods and maximum entropy aimed at senior undergraduates in science and engineering. It takes the mystery out of statistics by showing how a few fundamental rules can be used to tackle a variety of problems in data analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: 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. . . . . .

Condizione: 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.

paperback. Condizione: New. 2nd Edition. Special order direct from the distributor.

Condizione: NEW.

paperback. Condizione: New. In shrink wrap. Looks like an interesting title!

Paperback. Condizione: Brand New. 2nd edition. 246 pages. 9.00x6.00x1.00 inches. In Stock.

Paperback. Condizione: New. 2nd. 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'.

Condizione: new. Questo è un articolo print on demand.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Paperback. Condizione: new. Paperback. 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 illustratedwith a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximumlikelihood, 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'. This is the second edition of the first tutorial book on Bayesian methods and maximum entropy aimed at senior undergraduates in science and engineering. It takes the mystery out of statistics by showing how a few fundamental rules can be used to tackle a variety of problems in data analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: new. Paperback. 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 illustratedwith a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximumlikelihood, 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'. This is the second edition of the first tutorial book on Bayesian methods and maximum entropy aimed at senior undergraduates in science and engineering. It takes the mystery out of statistics by showing how a few fundamental rules can be used to tackle a variety of problems in data analysis. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This is the second edition of the first tutorial book on Bayesian methods and maximum entropy aimed at senior undergraduates in science and engineering. It takes the mystery out of statistics by showing how a few fundamental rules can be used to tackle a va.

Condizione: New. Print on Demand pp. 264.

Condizione: New. Print on Demand pp. 264 2nd Edition.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 imageprocessing. 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 techniquefor Bayesian computation called 'nested sampling'.