Overview
- Self-contained course-based graduate text
- Contains many exercices and worked examples
- Authored by an expert in the field
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Physics (LNP, volume 909)
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Keywords
- Bayesian Versus Frequentist Probability Theory
- Data Analysis in High Energy Physics
- Data Analysis in High Energy Physics
- Experimental Particle Physics and Data Anaylsis
- Hypothesis Testing and Discovery-based Science
- Modified Frequentist Approach
- Parameter Estimation and Uncertainties
- Statistics Textbook for Particle Physics
Table of contents (8 chapters)
Reviews
“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)
Authors and Affiliations
Bibliographic Information
Book Title: Statistical Methods for Data Analysis in Particle Physics
Authors: Luca Lista
Series Title: Lecture Notes in Physics
DOI: https://doi.org/10.1007/978-3-319-20176-4
Publisher: Springer Cham
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer International Publishing Switzerland 2016
eBook ISBN: 978-3-319-20176-4Published: 24 July 2015
Series ISSN: 0075-8450
Series E-ISSN: 1616-6361
Edition Number: 1
Number of Pages: XIX, 172
Number of Illustrations: 4 b/w illustrations, 59 illustrations in colour
Topics: Elementary Particles, Quantum Field Theory, Measurement Science and Instrumentation, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences