Skip to main content

Statistical Methods for Data Analysis in Particle Physics

  • Book
  • © 2016

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)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (8 chapters)

Keywords

About this book

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.

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

  • INFN Sezione di Napoli, Napoli, Italy

    Luca Lista

Bibliographic Information

Publish with us