Applied Nonparametric Statistical Methods
4th Edition
Published on 6. March 2007
Book
Hardback
542 pages
978-1-58488-701-0 (ISBN)
Description
While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets.
Reorganized and with additional material, this edition begins with a brief summary of some relevant general statistical concepts and an introduction to basic ideas of nonparametric or distribution-free methods. Designed experiments, including those with factorial treatment structures, are now the focus of an entire chapter. The text also expands coverage on the analysis of survival data and the bootstrap method. The new final chapter focuses on important modern developments, such as large sample methods and computer-intensive applications.
Keeping mathematics to a minimum, this text introduces nonparametric methods to undergraduate students who are taking either mainstream statistics courses or statistics courses within other disciplines. By giving the proper attention to data collection and the interpretation of analyses, it provides a full introduction to nonparametric methods.
Reorganized and with additional material, this edition begins with a brief summary of some relevant general statistical concepts and an introduction to basic ideas of nonparametric or distribution-free methods. Designed experiments, including those with factorial treatment structures, are now the focus of an entire chapter. The text also expands coverage on the analysis of survival data and the bootstrap method. The new final chapter focuses on important modern developments, such as large sample methods and computer-intensive applications.
Keeping mathematics to a minimum, this text introduces nonparametric methods to undergraduate students who are taking either mainstream statistics courses or statistics courses within other disciplines. By giving the proper attention to data collection and the interpretation of analyses, it provides a full introduction to nonparametric methods.
Reviews / Votes
... 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 EditionStrengths 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 ... 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 EditionStrengths 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
More details
Series
Edition
4th edition
Language
English
Place of publication
Boca Raton
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Undergraduate
Product notice
Unsewn / adhesive bound
Paper over boards
Illustrations
35 s/w Abbildungen
35 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 34 mm
Weight
975 gr
ISBN-13
978-1-58488-701-0 (9781584887010)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Nigel Smeeton | Neil H. Spencer | Peter Sprent
Applied Nonparametric Statistical Methods
Book
03/2025
5th Edition
Chapman & Hall/CRC
€128.60
Shipment within 15-20 days
Previous edition
Peter Sprent | Nigel C. Smeeton
Applied Nonparametric Statistical Methods, Third Edition
Book
09/2000
3rd Edition
CRC Press
€71.98
Article exhausted; check for reprint
Persons
Peter Sprent, Nigel C. Smeeton
Content
Some basic concepts. Fundamentals of nonparametric methods. Location inference for single samples. Other single-sample inferences. Methods for paired samples. Methods for two independent samples. Basic tests for three or more samples. Analysis of structured data. Analysis of survival data. Correlation and concordance. Bivariate linear regression. Categorical data. Association in categorical data. Robust estimation. Modern nonparametrics.