• An easy to read tutorial introduction to data anlaysis.
• Concise, being one of the slimmest books in the field!
• Self-contained - assumes little or no previous statistical training.
• Good illustrative examples where the basic concepts are explained with a series of examples that become progressively more advanced, but that are always kept as simple as possible to aid understanding.
• A contribution from John Skilling, an expert in numerical techniques. He introduces the simple but powerful new 'nested sampling' technique for Bayesian computaton.

New to this edition

• Completely updated graduate text.
• Three new chapters, two of which are from new co-author, John Skilling.

Readership: Senior undergraduate and graduate students in physics, chemistry, and engineering. Researchers across a broad spectrum of experimental scientific disciplines.

Devinderjit Sivia, Rutherford Appleton Laboratory and St Catherine's College, Oxford, and John Skilling, Maximum Entropy Data Consultants

"One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples." - Katie St. Clair MAA Reviews

1: Sivia: The Basics
2: Sivia: Parameter Estimation I
3: Sivia: Parameter Estimation II
4: Sivia: Model Selection
5: Sivia: Assigning Probabilities
6: Sivia: Non-parametric Estimation
7: Sivia: Experimental Design
8: Sivia: Least-Squares Extensions
9: Skilling: Nested Sampling
10: Skilling: Quantification
Appendices
Bibliography

Click here to visit the author's website