ISBN: 9780198568322 - Data Analysis:bayesian Tutorial 2e Paper: A Bayesian Tutorial (38 results)

Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condition: Very Good. 2nd edition, 264 pp., Paperback, hand stamp inside the front cover, else very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.…

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Paperback. Condition: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Condition: 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.…

Condition: As New. Unread book in perfect condition.

Paperback. Condition: 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'.…

Condition: New.

Condition: New. In English.

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Condition: 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. . . . . .

paperback. Condition: New. Special order direct from the distributor.

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

Condition: NEW.

Condition: 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.

Condition: As New. Unread book in perfect condition.

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

Condition: New. 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.

Paperback. Condition: 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'.…

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

Paperback. Condition: 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 multiple locations in the US or from the UK, depending on stock availability.…