Data Analysis: A Bayesian Tutorial

This book provides a logical and unified approach to data analysis using Bayesian probability theory.

It covers topics from parameter estimation to image processing, including reliability analysis, multivariate optimization, and experimental design.

The second edition includes a new chapter on handling outliers and correlated noise, along with contributions on 'nested sampling' for Bayesian computation.