Biostatistics: a computing approach.

Anderson, Stewart J., et al.

ISBN 10: 1584888342 ISBN 13: 9781584888345

Editorial: New York: Taylor and Francis, 2012., 2011

Idioma: Ingl�s

Condici�n: Usado Encuadernaci�n de tapa dura

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Descripci�n

Octavo, laminated boards,326 pp.,black and white illustrations, tables. The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25 years, broadening the landscape of available tools in statistical investigations of complex data. Biostatistics: A Computing Approach focuses on visualization and computational approaches associated with both modern and classical techniques. Furthermore, it promotes computing as a tool for performing both analyses and simulations that can facilitate such understanding. As a practical matter, programs in R and SAS are presented throughout the text. In addition to these programs, appendices describing the basic use of SAS and R are provided. Teaching by example, this book emphasizes the importance of simulation and numerical exploration in a modern-day statistical investigation. A few statistical methods that can be implemented with simple calculations are also worked into the text to build insight about how the methods really work.

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Detalles bibliogr�ficos

T�tulo: Biostatistics: a computing approach.
Editor: New York: Taylor and Francis, 2012.
Fecha de publicaci�n: 2011
Idioma: Ingl�s
ISBN 10: 1584888342
ISBN 13: 9781584888345
Encuadernaci�n: Encuadernaci�n de tapa dura

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Sinopsis

The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25 years, broadening the landscape of available tools in statistical investigations of complex data. Biostatistics: A Computing Approach focuses on visualization and computational approaches associated with both modern and classical techniques. Furthermore, it promotes computing as a tool for performing both analyses and simulations that can facilitate such understanding.

As a practical matter, programs in R and SAS are presented throughout the text. In addition to these programs, appendices describing the basic use of SAS and R are provided. Teaching by example, this book emphasizes the importance of simulation and numerical exploration in a modern-day statistical investigation. A few statistical methods that can be implemented with simple calculations are also worked into the text to build insight about how the methods really work.

Suitable for students who have an interest in the application of statistical methods but do not necessarily intend to become statisticians, this book has been developed from Introduction to Biostatistics II, which the author taught for more than a decade at the University of Pittsburgh.

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Stewart Anderson

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