دانلود کتاب Data Analysis in High Energy Physics, A Practical Guide to Statistical Methods

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 BarlowChapter 2 Parameter Estimation (pages 27–73): Dr. Olaf Behnke and Lorenzo MonetaChapter 3 Hypothesis Testing (pages 75–105): Dr. Gregory SchottChapter 4 Interval Estimation (pages 107–151): Luc DemortierChapter 5 Classification (pages 153–186): Helge VossChapter 6 Unfolding (pages 187–225): Volker BlobelChapter 7 Constrained Fits (pages 227–262): Benno ListChapter 8 How to Deal with Systematic Uncertainties (pages 263–296): Rainer WankeChapter 9 Theory Uncertainties (pages 297–328): Markus DiehlChapter 10 Statistical Methods Commonly Used in High Energy Physics (pages 329–356): Carsten Hensel and Dr. Kevin KroningerChapter 11 Analysis Walk?Throughs (pages 357–379): Aart Heijboer and Ivo van VulpenChapter 12 Applications in Astronomy (pages 381–407): Harrison B. Prosper