Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

DPD courier 4.99 € GLS courier 9.99 €

Contact

How to shop

Help

My account

▸ Empty :-(

Data Analysis

Name: Data Analysis
Brand: Oxford University Press
SKU: 01323043
Price: 53.7 EUR
Availability: InStock
Author: Devinderjit Sivia
ISBN: 9780198568322

Devinderjit Sivia

Language

English

Book Paperback

Libristo code: 01323043

Publishers Oxford University Press, June 2006

Statistics lectures have been a source of much bewilderment and frustration for generations of stude... Full description

Libristo code: 01323043

130 b

53.70 €

In stock at our supplier Shipping in 10-18 days

Up to 30 days for returns

Customers also purchased

Especial DELE A2 Curso completo - libro + audio descargable (2020 ed.) Mónica María García-Vinó Sánchez

Paperback

24.21 €

Okkult filozófia II. Agrippa von Nettesheim

Paperback

5.77 €

Oso pardo, oso pardo, que ves ahi? Bill Martin

Board book

9.21 €

Japonia. Przewodnik po bóstwach, duchach i bohaterach Joshua Frydman

Paperback

10.73 €

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'.