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

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

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

Author(s): Olaf Behnke (Editor), Kevin Krouml, ninger (Editor), Greacute, gory Schott (Editor), Thomas Schouml, rner-Sadenius (Editor)

  • Publisher: Wiley-VCH
  • Publication Date: 18 Jun. 2013
  • Edition: 1st
  • Language: English
  • Print length: 448 pages
  • ISBN-10: 3527410589
  • ISBN-13: 9783527410583

Book Description

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/

Editorial Reviews

From the Inside Flap

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.

From the contents:
_ Fundamental concepts
_ Parameter estimation
_ Hypothesis testing
_ Interval estimation
_ Classification
_ Unfolding
_ Constrained fits
_ How to deal with systematic uncertainties
_ Theory uncertainties
_ Statistical methods commonly used in high energy physics
_ Analysis walk-throughs
_ Applications in astronomy

From the Back Cover

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.

From the contents:
_ Fundamental concepts
_ Parameter estimation
_ Hypothesis testing
_ Interval estimation
_ Classification
_ Unfolding
_ Constrained fits
_ How to deal with systematic uncertainties
_ Theory uncertainties
_ Statistical methods commonly used in high energy physics
_ Analysis walk-throughs
_ Applications in astronomy

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