Statistical Methods for Data Analysis: With Applications in Particle Physics

This third edition expands on the original material, with more emphasis on machine learning and Monte Carlo methods. It provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data in HEP, including probability theory, basic statistics, Monte Carlo methods, and advanced concepts and applications. Many worked-out examples help newcomers and graduate students understand the pitfalls involved in applying theoretical concepts to actual data.

Format: Paperback / softback
Length: 334 pages
Publication date: 27 April 2023
Publisher: Springer International Publishing AG

This third edition is a significant expansion of the original content, with extensive revisions and clarifications throughout. The book now places greater emphasis on machine learning, incorporating more modern concepts and examples. Its primary goal is to equip readers with the essential concepts and tools required for conducting statistical analyses of experimental data, particularly in the field of high-energy physics (HEP).

The book begins with an introductory chapter on probability theory and basic statistics, designed to serve as a refresher for readers with advanced undergraduate backgrounds, as well as to help them differentiate between the Frequentist and Bayesian approaches and interpretations in subsequent applications. This introductory chapter also provides a solid foundation for the subsequent chapters, which delve into more advanced topics.

The author then delves into Monte Carlo methods, with a particular focus on techniques such as Markov Chain Monte Carlo (MCMC). The book introduces the concept of the best linear unbiased estimator (BLUE) and demonstrates its application in various scenarios. As the book progresses, more advanced concepts and applications are introduced, including unfolding and regularization procedures. These concepts are essential for analyzing complex data sets and extracting meaningful insights.

The final chapter of the book is dedicated to discoveries and upper limits, highlighting the importance of hypothesis testing in HEP and the calculation of look-elsewhere effects. Numerous worked-out examples are provided throughout the book to assist newcomers to the field and graduate students alike in understanding the challenges and pitfalls associated with applying theoretical concepts to actual data.

Overall, this third edition of the book is an invaluable resource for anyone interested in statistical analyses of experimental data, particularly in the field of HEP. It provides a comprehensive and up-to-date coverage of the relevant concepts and tools, making it an essential reference for researchers, students, and practitioners in the field.

Weight: 550g
Dimension: 155 x 234 x 23 (mm)
ISBN-13: 9783031199332
Edition number: 3rd ed. 2023