Introduction to Nonparametric Statistics for the Biological Sciences Using R (Hardcover, 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	July 2016
First published:	2016
Authors:	Thomas W. MacFarland • Jan M. Yates
Dimensions:	235 x 155 x 25mm (L x W x T)
Format:	Hardcover
Pages:	329
Edition:	1st ed. 2016
ISBN-13:	978-3-319-30633-9
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Promotions
LSN:	3-319-30633-2
Barcode:	9783319306339

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