Description

Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models. In 'An Introduction to Mathematical Statistics' the authors describe key concepts from statistics and give a mathematical basis for important statistical methods. Much attention is paid to the sound application of those methods to data.

The three main topics in statistics are estimators, tests, and confidence regions. The authors illustrate these in many examples, with a separate chapter on regression models, including linear regression and analysis of variance. They also discuss the optimality of estimators and tests, as well as the selection of the best-fitting model.Each chapter ends with a case study in which the described statistical methods are applied.

This book assumes a basic knowledge of probability theory, calculus, and linear algebra.

An Introduction to Mathematical Statistics

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£31.99

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Paperback / softback by Fetsje Bijma , Marianne Jonker

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Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models.... Read more

    Publisher: Amsterdam University Press
    Publication Date: 15/05/2017
    ISBN13: 9789462985100, 978-9462985100
    ISBN10: 9462985103

    Number of Pages: 384

    Non Fiction , Mathematics & Science , Education

    Description

    Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models. In 'An Introduction to Mathematical Statistics' the authors describe key concepts from statistics and give a mathematical basis for important statistical methods. Much attention is paid to the sound application of those methods to data.

    The three main topics in statistics are estimators, tests, and confidence regions. The authors illustrate these in many examples, with a separate chapter on regression models, including linear regression and analysis of variance. They also discuss the optimality of estimators and tests, as well as the selection of the best-fitting model.Each chapter ends with a case study in which the described statistical methods are applied.

    This book assumes a basic knowledge of probability theory, calculus, and linear algebra.

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