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Titlebook: Statistical Methods for Data Analysis in Particle Physics; Luca Lista Book 20172nd edition Springer International Publishing AG 2017 Bayes

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书目名称Statistical Methods for Data Analysis in Particle Physics
编辑Luca Lista
视频video
概述Self-contained course-based graduate text.Contains many exercises and worked-out examples.New second edition significantly expands on the original material, with more background content applications a
丛书名称Lecture Notes in Physics
图书封面Titlebook: Statistical Methods for Data Analysis in Particle Physics;  Luca Lista Book 20172nd edition Springer International Publishing AG 2017 Bayes
描述.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 line
出版日期Book 20172nd edition
关键词Bayesian Versus Frequentist Probability Theory; Data Analysis in High Energy Physics; Experimental Par
版次2
doihttps://doi.org/10.1007/978-3-319-62840-0
isbn_ebook978-3-319-62840-0Series ISSN 0075-8450 Series E-ISSN 1616-6361
issn_series 0075-8450
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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