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.