Data Analysis A Bayesian Tutorial,9780198568322

Data Analysis A Bayesian Tutorial

by ;
Edition: 2nd
ISBN13: 9780198568322
ISBN10: 0198568320
Format: Paperback
Pub. Date: 2006-07-27
Publisher(s): Oxford University Press
List Price: $69.15

Buy New

Usually Ships in 5-7 Business Days
$65.86
Add to Cart

Buy Used

Usually Ships in 24-48 Hours
$48.00
Add to Cart

Rent Textbook

Select for Price
Add to Cart
There was a problem. Please try again later.

Digital

Rent Digital Options
Online:180 Days access
Downloadable:180 Days
$32.99
Online:365 Days access
Downloadable:365 Days
$37.50
Online:1460 Days access
Downloadable:Lifetime Access
$49.99
*To support the delivery of the digital material to you, a non-refundable digital delivery fee of $3.99 will be charged on each digital item.
$39.59*
Add to Cart
Buy from our Marketplace starting at $22.49

How Marketplace Works:

  • This item is offered by an independent seller and not shipped from our warehouse
  • Item details like edition and cover design may differ from our description; see seller's comments before ordering.
  • Sellers much confirm and ship within two business days; otherwise, the order will be cancelled and refunded.
  • Marketplace purchases cannot be returned to eCampus.com. Contact the seller directly for inquiries; if no response within two days, contact customer service.
  • Additional shipping costs apply to Marketplace purchases. Review shipping costs at checkout.

Summary

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'.

Author Biography


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

Table of Contents

Sivia: The Basics
Sivia: Parameter Estimation I
Sivia: Parameter Estimation II
Sivia: Model Selection
Sivia: Assigning Probabilities
Sivia: Non-parametric Estimation
Sivia: Experimental Design
Sivia: Least-Squares Extensions
Skilling: Nested Sampling
Skilling: Quantification
Appendices
Bibliography
Table of Contents provided by Publisher. All Rights Reserved.

An electronic version of this book is available through VitalSource.

This book is viewable on PC, Mac, iPhone, iPad, iPod Touch, and most smartphones.

By purchasing, you will be able to view this book online, as well as download it, for the chosen number of days.

Digital License

You are licensing a digital product for a set duration. Durations are set forth in the product description, with "Lifetime" typically meaning five (5) years of online access and permanent download to a supported device. All licenses are non-transferable.

More details can be found here.

A downloadable version of this book is available through the eCampus Reader or compatible Adobe readers.

Applications are available on iOS, Android, PC, Mac, and Windows Mobile platforms.

Please view the compatibility matrix prior to purchase.