Statistical Methods for Data Analysis in Particle Physics

Statistical Methods for Data Analysis in Particle Physics

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Description

This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.
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Product details

  • Paperback | 172 pages
  • 155 x 235 x 10.41mm | 302g
  • Cham, Switzerland
  • English
  • 1st ed. 2016
  • 59 Illustrations, color; 4 Illustrations, black and white; XIX, 172 p. 63 illus., 59 illus. in color.
  • 3319201751
  • 9783319201757

Back cover copy

This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.
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Table of contents

Preface.- Probability theory.- Probability Distribution Functions.- Bayesian approach to probability.- Random numbers and Monte Carlo Methods.- Parameter estimate.- Confidence intervals.- Hypothesis tests.- Upper Limits.- Bibliography.
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Review Text

"This book is an excellent introduction to statistical methods for data analysis in general, not only in particle physics. ... The contents are well structured, concise and easily understandable. Particular effort was made in illustrating distinct characters of frequency and Bayesian approaches. ... I highly recommend this book to anyone who is interested in pursuing data analysis in all fields." (Zhen Mei, zbMATH 1333.81007, 2016)
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Review quote

"This book is an excellent introduction to statistical methods for data analysis in general, not only in particle physics. ... The contents are well structured, concise and easily understandable. Particular effort was made in illustrating distinct characters of frequency and Bayesian approaches. ... I highly recommend this book to anyone who is interested in pursuing data analysis in all fields." (Zhen Mei, zbMATH 1333.81007, 2016)
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