Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods


thumbnail image: Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods
  • Published: 19 June 2013
  • ISBN: 9783527410583
  • Author(s): Olaf Behnke, Kevin Kroninger, Gregory Schott, Thomas Schorner-Sadenius
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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

1 Fundamental concepts
Roger Barlow

2 Parameter estimation
Olaf Behnke and Lorenzo Moneta

3 Hypothesis testing
Gregory Schott

4 Interval Estimation
Luc Demortier

5 Classification
Helge Voss

6 Unfolding
Volker Blobel

7 Constrained fits
Benno List

8 How to deal with systematic uncertainties
Rainer Wanke

9 Theory uncertainties
Markus Diehl

10 Statistical methods commonly used in high energy physics
Carsten Hensel and Kevin Kroninger

11 Analysis walk-throughs
Aart Heijboer and Ivo van Vulpen

12 Applications in astronomy
Harrison B. Prosper

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