- Self-contained course-based graduate text
- Contains many exercises and worked-out examples
- New second edition significantly expands on the original material, with more background content applications and examples (e.g. look-elsewhere effect).
Buy this book
- About this book
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This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP).
First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether.
Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical concepts to actual data.
This new second edition significantly expands on the original material, with more background content (e.g. the Markov Chain Monte Carlo method, best linear unbiased estimator), applications (unfolding and regularization procedures, control regions and simultaneous fits, machine learning concepts) and examples (e.g. look-elsewhere effect calculation).
- About the authors
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Luca Lista works on the CMS experiment at CERN's Large Hadron Collider, specifically on the search for dark matter and on top-quark physics. He has been involved in testing the Standard Model of particle physics and in the search for the Higgs boson.
- Table of contents (10 chapters)
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Probability Theory
Pages 1-23
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Probability Distribution Functions
Pages 25-58
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Bayesian Approach to Probability
Pages 59-80
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Random Numbers and Monte Carlo Methods
Pages 81-95
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Parameter Estimate
Pages 97-127
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Table of contents (10 chapters)
- Download Preface 1 PDF (38.2 KB)
- Download Sample pages 1 PDF (2.4 MB)
- Download Table of contents PDF (72.8 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Statistical Methods for Data Analysis in Particle Physics
- Authors
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- Luca Lista
- Series Title
- Lecture Notes in Physics
- Series Volume
- 941
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-62840-0
- DOI
- 10.1007/978-3-319-62840-0
- Softcover ISBN
- 978-3-319-62839-4
- Series ISSN
- 0075-8450
- Edition Number
- 2
- Number of Pages
- XVI, 257
- Number of Illustrations
- 4 b/w illustrations, 97 illustrations in colour
- Topics
*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works and instructor copies are not included.
