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 1โ26): Roger Barlow
Chapter 2 Parameter Estimation (pages 27โ73): Dr. Olaf Behnke and Lorenzo Moneta
Chapter 3 Hypothesis Testing (pages 75โ105): Dr. Gregory Schott
Chapter 4 Interval Estimation (pages 107โ151): Luc Demortier
Chapter 5 Classification (pages 153โ186): Helge Voss
Chapter 6 Unfolding (pages 187โ225): Volker Blobel
Chapter 7 Constrained Fits (pages 227โ262): Benno List
Chapter 8 How to Deal with Systematic Uncertainties (pages 263โ296): Rainer Wanke
Chapter 9 Theory Uncertainties (pages 297โ328): Markus Diehl
Chapter 10 Statistical Methods Commonly Used in High Energy Physics (pages 329โ356): Carsten Hensel and Dr. Kevin Kroninger
Chapter 11 Analysis Walk?Throughs (pages 357โ379): Aart Heijboer and Ivo van Vulpen
Chapter 12 Applications in Astronomy (pages 381โ407): Harrison B. Prosper