000			03011 a2200277 4500
001			1040267750
005			20250328151419.0
008			250324022025xx 62 eng
020			_a9781040267752 _qEA
037			_bTaylor & Francis _cGBP 84.99 _fBB
040			_a01
041			_aeng
072	7		_aPBT _2thema
072	7		_aPS _2thema
072	7		_aPBT _2bic
072	7		_aPS _2bic
072	7		_aMAT029000 _2bisac
100	1		_aNeil Spencer
245	1	0	_aApplied Nonparametric Statistical Methods
250			_a5
260			_bChapman and Hall/CRC _c20250331
300			_a476 p
520			_bNonparametric statistical methods minimize 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 A case study from medical research to demonstrate nonparametric approaches to the data analysis Examples fully integrated into the text, drawn from published research on contemporary issues, with more detail given in their explanation Extensive exercises along with complete solutions that allow the reader to test their understanding of the material Articles used in the examples and exercises carefully chosen to enable readers to identify up-to-date literature in their field for research, publications and teaching material Numerous historical references throughout the text, from which to explore the origins of nonparametric methods Applied Nonparametric Statistical Methods, Fifth Edition , is a comprehensive course text in nonparametric techniques suitable for undergraduate students of mathematics and statistics. It assumes only basic previous experience of statistics, and with algebra kept to a minimum, it is also ideal for quantitative methods modules delivered to undergraduate or postgraduate students in science, business and health service training. It is an invaluable resource for researchers, medical practitioners, business managers, research and development staff, and others needing to interpret quantitative information. Suitable for self-directed learning in continuing professional development, it also acts as a handy accessible reference manual.
700	1		_aNigel C. Smeeton _4A01
700	1		_aPeter Sprent _4A01
999			_c8037 _d8037