Statistical Methods For Data Analysis In Particle Physics
Download Statistical Methods For Data Analysis In Particle Physics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Statistical Methods For Data Analysis In Particle Physics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Data Analysis in High Energy Physics
This practical guide covers the essential tasks in statistical data analysis encountered in high energy physics and provides comprehensive advice for typical questions and problems. The basic methods for inferring results from data are presented as well as tools for advanced tasks such as improving the signal-to-background ratio, correcting detector effects, determining systematics and many others. Concrete applications are discussed in analysis walkthroughs. Each chapter is supplemented by numerous examples and exercises and by a list of literature and relevant links. The book targets a broad readership at all career levels - from students to senior researchers. An accompanying website provides more algorithms as well as up-to-date information and links. * Free solutions manual available for lecturers at www.wiley-vch.de/supplements/
Statistical Methods for Data Analysis in Particle Physics
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).
Statistics for Nuclear and Particle Physicists
Author: Louis Lyons
language: en
Publisher: Cambridge University Press
Release Date: 1989-04-06
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.