Massimiliano Bonamente Bonamente Statistics and Analysis of Scientific Data

Statistics and Analysis of Scientific Data

von Massimiliano Bonamente

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Beschreibung

Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topics covered include probability theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practical application, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data.

The main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the students' understanding of the topic.


Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topics covered include probability theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practical application, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data.

The main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the students' understanding of the topic.


Includes numerical tables of data for critical distribution functions, making the textbook a self-contained guide for students Covers the theory and practice of Monte Carlo Markov chains, a leading tool for the analysis of complex data sets, and a topic virtually absent in other textbooks Covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data

Autor*in

Massimiliano Bonamente

Themen in »Statistics and Analysis of Scientific Data«

2-variable dataset Monte Carlo Markov chain methods Probability and applied statistics textbook data analysis methods distribution functions of statistics numerical Monte Carlo methods probability textbook random variable theories of probability statistical applications physics statistical data textbook

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Details

ISBN: 9781461479840
Verlag: Springer US
Erscheinung: 13.08.2013

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