Statistics for Nuclear and Particle Physicists

Author: Louis Lyons
Publisher: Cambridge University Press
ISBN: 9780521379342
Format: PDF, ePub, Mobi
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This practical approach to statistical problems arising regularly in analyzing data from nuclear and high energy physics experiments is geared toward non-statisticians.

Statistics for Nuclear and Particle Physicists

Author: Louis Lyons
Publisher: Cambridge University Press
ISBN: 1316101630
Format: PDF, ePub
Download Now
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.

Statistics for Nuclear and Particle Physicists

Author: Louis Lyons
Publisher: Cambridge University Press
ISBN: 9780521255400
Format: PDF, Docs
Download Now
Written by a non-statistician for non-statisticians, the book emphasizes the practical approach to those problems in statistics that arise regularly in data analysis situations in nuclear and high energy physics experiments. Rather than concentrate on proofs and theorems, the author provides an abundance of simple examples that illustrate the general ideas presented. This allows the reader to obtain maximum information in the simplest manner. Possible difficulties with the various techniques, and pitfalls to be avoided, are also discussed. This commonsense approach to statistical formalism enables nuclear physicists to better understand how to do justice to their analysis and interpretation of data.

Statistical Analysis Techniques in Particle Physics

Author: Ilya Narsky
Publisher: John Wiley & Sons
ISBN: 3527677291
Format: PDF, ePub
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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.

Techniques for Nuclear and Particle Physics Experiments

Author: William R. Leo
Publisher: Springer Science & Business Media
ISBN: 3642579205
Format: PDF, Docs
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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.

Experimental Techniques in Nuclear and Particle Physics

Author: Stefaan Tavernier
Publisher: Springer Science & Business Media
ISBN: 9783642008290
Format: PDF, ePub, Docs
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I have been teaching courses on experimental techniques in nuclear and particle physics to master students in physics and in engineering for many years. This book grew out of the lecture notes I made for these students. The physics and engineering students have rather different expectations of what such a course should be like. I hope that I have nevertheless managed to write a book that can satisfy the needs of these different target audiences. The lectures themselves, of course, need to be adapted to the needs of each group of students. An engineering student will not qu- tion a statement like “the velocity of the electrons in atoms is ?1% of the velocity of light”, a physics student will. Regarding units, I have written factors h and c explicitly in all equations throughout the book. For physics students it would be preferable to use the convention that is common in physics and omit these constants in the equations, but that would probably be confusing for the engineering students. Physics students tend to be more interested in theoretical physics courses. However, physics is an experimental science and physics students should und- stand how experiments work, and be able to make experiments work.

Data Analysis in High Energy Physics

Author: Olaf Behnke
Publisher: John Wiley & Sons
ISBN: 3527653430
Format: PDF, ePub
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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 Data Analysis

Author: Glen Cowan
Publisher: Oxford University Press
ISBN: 0198501560
Format: PDF, Docs
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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 taken from 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).

Statistical Methods for Data Analysis in Particle Physics

Author: Luca Lista
Publisher: Springer
ISBN: 3319628402
Format: PDF, Docs
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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).

Probability and Statistics for Particle Physics

Author: Carlos Maña
Publisher: Springer
ISBN: 3319557386
Format: PDF, Docs
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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.