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Introduction to Nonparametric Statistics for the Biological Sciences Using R
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Bibliographic Detail
Publisher Springer Verlag
Publication date June 2, 2016
Binding Hardcover
Book category Adult Non-Fiction
ISBN-13 9783319306339
ISBN-10 3319306332
Dimensions 0 by 6.10 by 9.25 in.
Original list price $79.99
Summaries and Reviews
Amazon.com description: Product Description:

This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences:

  • To introduce when nonparametric approaches to data analysis are appropriate
  • To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test
  • To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set

The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.



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Hardcover
Book cover for 9783319306339
 
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With Thomas W. Macfarland | from Springer Verlag (June 2, 2016)
9783319306339 | details & prices | List price $79.99
About: This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriateTo introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each testTo introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively.

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