Data Analysis In High Energy Physics A Practical Guide To Statistical Methods Olaf Behnke by Olaf Behnke, Kevin Kroninger, Gregory Schott, Thomas Schorner-sadenius 9783527410583, 9783527653416, 3527410589, 3527653414 instant download after payment.

This practical guide covers the essential tasks in statistical data analysis encountered in high energy physics and provides comprehensive advice for typical questions and problems. The basic methods for inferring results from data are presented as well as tools for advanced tasks such as improving the signal-to-background ratio, correcting detector effects, determining systematics and many others. Concrete applications are discussed in analysis walkthroughs. Each chapter is supplemented by numerous examples and exercises and by a list of literature and relevant links. The book targets a broad readership at all career levels - from students to senior researchers. An accompanying website provides more algorithms as well as up-to-date information and links.

* Free solutions manual available for lecturers at www.wiley-vch.de/supplements/

Content:
Chapter 1 Fundamental Concepts (pages 1–26): Roger Barlow
Chapter 2 Parameter Estimation (pages 27–73): Dr. Olaf Behnke and Lorenzo Moneta
Chapter 3 Hypothesis Testing (pages 75–105): Dr. Gregory Schott
Chapter 4 Interval Estimation (pages 107–151): Luc Demortier
Chapter 5 Classification (pages 153–186): Helge Voss
Chapter 6 Unfolding (pages 187–225): Volker Blobel
Chapter 7 Constrained Fits (pages 227–262): Benno List
Chapter 8 How to Deal with Systematic Uncertainties (pages 263–296): Rainer Wanke
Chapter 9 Theory Uncertainties (pages 297–328): Markus Diehl
Chapter 10 Statistical Methods Commonly Used in High Energy Physics (pages 329–356): Carsten Hensel and Dr. Kevin Kroninger
Chapter 11 Analysis Walk?Throughs (pages 357–379): Aart Heijboer and Ivo van Vulpen
Chapter 12 Applications in Astronomy (pages 381–407): Harrison B. Prosper