86,89 €
Statistics for Nuclear and Particle Physicists
Statistics for Nuclear and Particle Physicists
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Statistics for Nuclear and Particle Physicists
Statistics for Nuclear and Particle Physicists
El. knyga:
86,89 €
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, a…

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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.

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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.

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