Description
Book SynopsisNonparametric statistical methods minimise the number of assumptions that need to be made about the distribution of data being analysed, unlike classical parametric methods. As such, they are an essential part of a statistician's armoury and this book is an essential resource in their application. Starting from the basics of statistics, it takes the reader through the main nonparametric approaches with an emphasis on carefully explained examples backed up by use of the R programming language.
Key features of this fully revised and extended fifth edition include:
- An introductory chapter that provides a gentle introduction to the basics of statistics, including types of data, hypothesis testing, confidence intervals, and ethical issues
- An R package containing functions that have been written for the examples in the text and the exercises
- Summary bullet points at the end of each section to enable the reader to locate important principles quickly
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