Statistical Data Analysis This guide to the practical application of statistics in data analysis, as typically encountered in the physical sciences, is primarily addressed at students and researchers who work with experimental data. The topics include probability, random variables, Monte Carlo techniques, statistical tests, parameter estimation, and unfolding methods. Full description
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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).
"Glen Cowan is a particle physicist who seems to have got everything right. Results are stated clearly, without mathematical proof but with enough explanation to satisfy the physicist's need to understand not only how, but also why...Those teaching an advanced undergraduate or graduate course in statistics or physicists will find this a good textbook...Do not be fooled by the fact that it does not have the "textbook look" - the exercises have been made available separately on a Web site. " CERN Courier
"The material presented in this book is dense.In less than two hundred pages, it takes the reader from the basic notions of probability, through neural networks, Monte Carlo methods, and regularization techniques." Short Book Reviews
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