Statistical Data Analysis

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Bol The 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 researchers who work with experimental data. The topics include probability, random variables, Monte Carlo techniques, statistical tests, parameter estimation, and unfolding methods. 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).

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Bol

The 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 researchers who work with experimental data. The topics include probability, random variables, Monte Carlo techniques, statistical tests, parameter estimation, and unfolding methods. 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).

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Pages: 212, Paperback, OUP Oxford


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Merk Oxford University Press, USA
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  • 9780198501558
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