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Applied Nonparametric Statistical Methods de Nigel Smeeton

Applied Nonparametric Statistical Methods: Chapman & Hall/CRC Texts in Statistical Science

Autor Nigel Smeeton, Peter Sprent
en Limba Engleză Hardback – 31 mar 2025
Nonparametric 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 the following:
  • 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  • Numerous historical references throughout the text, from which to explore the origins of nonparametric methods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.
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Specificații

ISBN-13: 9780367344894
ISBN-10: 0367344890
Pagini: 476
Ilustrații: 62
Dimensiuni: 178 x 254 x 34 mm
Greutate: 1.04 kg
Ediția:5
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Texts in Statistical Science

Locul publicării:Boca Raton, United States

Public țintă

Undergraduate

Cuprins

1. Basic concepts of statistical inference. 2. Fundamentals of nonparametric methods. 3. Exploring averages for single samples. 4. Other single-sample inferences. 5. Methods for paired samples. 6. Methods for two independent samples. 7. Basic tests for three or more samples. 8. Analysis of structured data. 9. Analysis of survival data. 10. Correlation and concordance. 11. Bivariate linear regression. 12. Categorical data. 13. Association in categorical data. 14. Robust estimation. 15. Nonparametric methods in action. 

Notă biografică

Nigel Smeeton commenced his career as the Statistical Assistant at Leeds University in the Department of Statistics, teaching statistics to undergraduate and postgraduate students, and running the statistical advisory service. He then joined the General Practice Research Unit at the Institute of Psychiatry, London, focusing on the modelling of episodes of mental illness, classification of mental illness, and repetition of attempted suicide. Moving to the United Medical and Dental Schools (now part of King's College London), he specialised in stroke and asthma epidemiology. Having established the undergraduate (BDS) course in dental statistics, he wrote the introductory text Dental Statistics Made Easy, which has run to three editions. With Peter Sprent, he co-authored the third and fourth editions of Applied Nonparametric Statistical Methods. He has been Editor of the applied statistics journal The Statistician.
He joined the Centre for Research in Public Health and Community Care, University of Hertfordshire in 2013. Having worked in the areas of adolescent behaviour and epilepsy risk, he is currently part of a UK National Institute for Health and Care Research (NIHR) funded team evaluating public health interventions. His statistical expertise and interests include capture-recapture methods, proportional hazards regression, kappa statistics and the historical development of statistical methods. 
 
Neil Spencer is Professor of Applied Statistics and Head of the Business Research Unit and Statistical Services and Consultancy Unit in Hertfordshire Business School at the University of Hertfordshire. He completed a BSc in Applied Statistics at the University of Reading before moving to the University of Southampton for an MSc in Social Statistics and then to Lancaster University for a PhD in Applied Statistics. He then became a lecturer at Staffordshire University, where he first became involved in consultancy, and moved on to the University of Hertfordshire. He is a Chartered Statistician.
He has undertaken research in a variety of subjects, from Victorian censuses to value-added school league tables, paramedics treating patients whilst wearing protective equipment, health behaviour surveys of school children, compassion in education, creation of family memories, and surveys of gig economy workers across 13 European countries. Consultancy work has included testing the randomness of National Lottery machines (for over two decades), parish plan surveys, appearing as an expert witness, methods for in-service testing of utility meters, and others, for a range of clients large and small. He is author of the books SAS Programming: The One-Day Course and Essentials of Multivariate Data Analysis.
 
Peter Sprent started out as Tutor, then Lecturer in Mathematics at the University of Tasmania, where he taught undergraduate students and provided statistical support within the University and to government departments and agencies. A sabbatical at the renown British agricultural institution Rothhamsted Experimental Station resulted in an appointment at East Malling Research Station, where he focused on the application of statistical methods to agricultural science. Moving to the University of Dundee, he developed the provision of teaching in statistics and headed up the statistical consultancy service within the University. His research areas included statistical regression, the analysis of small experiments, and the mathematics of size and shape. He was appointed to a personal Chair and continued working at the University of Dundee until his retirement, when he was awarded an Emeritus Professorship.
He devoted his later life to writing texts, mostly on nonparametric statistics. In addition, determined to raise the understanding of statistics in society as a whole he published the books Taking Risks: The Science of Uncertainty and Understanding Data. With his wife Janet, a botanist, he co-produced the text Nitrogen Fixing Organisms: Pure and Applied Aspects and a guide to the mountains of north-west Scotland.

Descriere

A comprehensive course text in nonparametric techniques suitable for undergraduate mathematics students. Assumes only basic experience of statistics with algebra kept to a minimum. Ideal for quantitative methods modules delivered to undergraduate or postgrad students in science, business, and health service training.

Recenzii

… The greatest strength of this book is that it is written at a level that is perfectly understandable by readers with only a course or two of introductory-level statistics. As such, it is appropriate for use as either a textbook for a first course in nonparametric methods for undergraduate statistics majors or as a reference for practitioners in other fields. It is also quite suitable as a supplementary statistics textbook for graduate students … . Key concepts are taught using worked-out examples from a variety of fields. … a worthwhile choice for either an introductory-level textbook or a self-study reference for nonspecialists. The writing is very accessible and not weighted down by any mathematics beyond the grasp of the intended audience. …
—Psychometrika, Vol. 75, No. 3, September 2010
… this book has an effective organization and covers a wider scope of non-parametric methods than former editions. Therefore, I believe that this book can serve its intended audience.
—Journal of the Royal Statistical Society, Series A, Vol. 173, Issue 1, January 2010
Most fourth editions look surprisingly similar to the third editions. Applied Nonparametric Statistical Methods is an exception. Sprent and Smeeton have taken an accessible and well-regarded work and expanded, reorganized, and improved on it. … Sprent and Smeeton offer a strong connection with respect to the how and why of the techniques. … The book’s major strength is its prioritization of coverage. The authors take painstaking care to inculcate an understanding of the appropriate use of nonparametric methods, as well as an appreciation for their application over a wide range of fields. The examples are well chosen, and the variety should ensure that every reader finds at least some of the problems interesting. … As a competitor to the texts by Conover (1999), Gibbons and Chakraborti (2004), Higgins (2004), and Wasserman (2006), Applied Nonparametric Statistical Methods more than holds its own. The combination of clear writing and comprehensive coverage make it an excellent introductory text. …
—Technometrics, Vol. 51, No. 2, May 2009
…The chapters have been substantially reorganized, and new material is provided on methods related to factorial designs and time-to-event data. An entirely new chapter, ‘Modern Nonparametrics,’ closes the text with a variety of topics … the worked examples are thoroughly and meticulously done … constant mention is made of the available software (e.g., StatXact, R, Minitab, SPSS) to conduct specific procedures. … solutions to selected end-of-chapter exercises are annotated and quite helpful. Overall, this is a solid choice for a first course in nonparametric statistics for undergraduates.
—Journal of the American Statistical Association, Vol. 104, No. 487, September 2009
… expands coverage on the analysis of survival data and the bootstrap method. … the new edition also focuses on some modern developments. The formal testing procedures are illustrated in a nice way with realistic examples leading to final conclusions, comments, and a discussion… The book has a clear style with well-organized material. The book works well as a reference book for users of nonparametric methods in different research areas. It is also a good textbook for undergraduate courses in statistics as well as courses for students majoring in other disciplines.
—Hannu Oja, International Statistical Review, Vol. 27, No. 1, 2008
Praise for the Third Edition
Strengths of this text certainly include its organization and writing style. Applied Nonparametric Statistical Methods provides a very clear exposition of modern nonparametric methods. Many students and practitioners will find it an excellent resource and reference for nonparametric statistics.
—Technometrics, 2003

… extremely valuable for statisticians as well as for researchers in applied fields. … This well-written book is highly recommended for those readers who want to get a feeling for the nonparametric methods which they apply when analysing their data.
—Statistics in Medicine, 2004