This book, written by a non-statistician for non-statisticians, emphasises the practical approach to those problems in statistics which arise regularly in data analysis situations in nuclear and high-energy physics experiments. Rather than concentrating on formal proofs of theorems, an abundant use of simple examples illustrates the general ideas which are presented, showing the reader how to obtain the maximum information from the data in the simplest manner. Possible difficulties with the various techniques, and pitfalls to be avoided, are also discussed. Based on a series of lectures given by the author to both students and staff at Oxford, this common-sense approach to statistics will enable nuclear physicists to understand better how to do justice to their data in both analysis and interpretation.

This book comprehensively presents the basic concepts of probability and Bayesian inference with sufficient generality to make them applicable to current problems in scientific research. The first chapter provides the fundamentals of probability theory that are essential for the analysis of random phenomena. The second chapter includes a full and pragmatic review of the Bayesian methods that constitute a natural and coherent framework with enough freedom to analyze all the information available from experimental data in a conceptually simple manner. The third chapter presents the basic Monte Carlo techniques used in scientific research, allowing a large variety of problems to be handled difficult to tackle by other procedures. The author also introduces a basic algorithm, which enables readers to simulate samples from simple distribution, and describes useful cases for researchers in particle physics.The final chapter is devoted to the basic ideas of Information Theory, which are important in the Bayesian methodology. This highly readable book is appropriate for graduate-level courses, while at the same time being useful for scientific researches in general and for physicists in particular since most of the examples are from the field of Particle Physics.

A treatment of the experimental techniques and instrumentation most often used in nuclear and particle physics experiments as well as in various other experiments, providing useful results and formulae, technical know-how and informative details. This second edition has been revised, while sections on Cherenkov radiation and radiation protection have been updated and extended.

Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.

An accessible introduction to nuclear and particle physics with equal coverage of both topics, this text covers all the standard topics in particle and nuclear physics thoroughly and provides a few extras, including chapters on experimental methods; applications of nuclear physics including fission, fusion and biomedical applications; and unsolved problems for the future. It includes basic concepts and theory combined with current and future applications. An excellent resource for physics and astronomy undergraduates in higher-level courses, this text also serves well as a general reference for graduate studies.

The book is based on a laboratory course in nuclear physics given to advanced students. It treats the experimental techniques and instrumentationmost often used in nuclear and particle physics experiments as well as in various other experimental sciences. It provides most useful results and formulae, technical know-how and informative details on -interactionof radiation in matter; - radion protection and radioactive sources; - statistics for the interpretation and analysis of data; - principles and operation of the main types of detectors (ionization, scintillation and semiconductor detectors); - nuclear electronics instrumentation (NIM, CAMAC); - various systems and techniques for experiments. Thanks to the author's long teaching experience the material is presented in a verypractical, hands-on way making the book a useful text and lab companion for students and experienced scientists.

This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).