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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 www.wiley-vch.de/supplements/
Info autore
Olaf Behnke is a staff physicist at DESY Hamburg. He studied physics at the University of Hamburg, received his PhD from ETH Zurich and habilitated at the University of Heidelberg. He has worked on experiments at DESY (ARGUS, H1 and ZEUS) and at CERN (CP-LEAR). His main interest and expertise is in physics data analysis where his experiences range from the basic analysis level to the coordination of a large experiment (H1). Olaf Behnke is currently working at the ZEUS experiment on the final data analysis of charm and beauty quark production in ep collisions at HERA.
Kevin Kroeninger studied physics at the Universities of Goettingen and Bonn, and the Northeastern University, Boston. He received his PhD from the University of Technology, Munich, where he performed research at the Max-Planck-Institute for Physics. Kevin Kroeninger has worked on experiments at DESY (Hermes), FNAL (D0), CERN (ATLAS, CMS) and the LNGS (Gerda). His expertise is in germanium semiconductor detectors in the context of low background and neutrino experiments, and top quark physics at hadron collider experiments. Kevin Kroeninger is currently working in the ATLAS group of the University of Göttingen where he is preparing the analysis of the first LHC data and working on the development of tools for statistical data analysis.
Grégory Schott is a physicist employed at Karlsruhe Institute of Technology. After completing his PhD at CEA/Saclay (France) and a first postdoc in the BaBar experiment, he joined the CMS experiment in 2007 where he has been working on preparation analysis for Higgs searches. He looked at the possibility of combining the related measurements and worked on applying and comparing results of different statistical approaches. He is one of the authors of the RooStats software package that is a general purpose tool for statistical interpretation in data analysis with various approaches used in High Energy Physics. He is currently a member of the statistics committee of the CMS experiment.
Riassunto
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/
