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ISBN:1584881453
Author: Nigel C. Smeeton,Peter Sprent
ISBN13: 978-1584881452
Title: Applied Nonparametric Statistical Methods, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
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Language: English
Category: Mathematics
Publisher: Chapman and Hall/CRC; 3 edition (September 7, 2000)
Pages: 480

Applied Nonparametric Statistical Methods, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) by Nigel C. Smeeton,Peter Sprent



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. It aims at promoting understanding as well. Good statistical practice is exemplified throughout… Particularly commendable are their discussions of multiple comparisons and conditioning in the two by two contingency table… If I could only have one book on nonparametric methods, this would be my choice. It is highly recommended. Series: Chapman & Hall/CRC Texts in Statistical Science. Paperback: 480 pages.

Author: Nigel C. Smeeton, Peter Sprent.

Chapman & Hall/CRC Texts in Statistical Science.

Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density estimation, and resampling methods. Download from free file storage.

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This new edition follows the basic easy-to-digest pattern that was so well received by users of the earlier editions. The authors substantially update and expand Applied Nonparametric Statistical Methods to reflect changing attitudes towards applied statistics, new developments, and the impact of more widely available and better statistical software.The book takes into account computing developments since the publication of the popular Second Edition, rearranging the material in a more logical order, and introducing new topics. It emphasizes better use of significance tests and focuses greater attention on medical and dental applications. Applied Nonparametric Statistical Methods: Third Edition explains the rationale of procedures with a minimum of mathematical detail, making it not only an outstanding textbook, but also an up-to-date reference for professionals who do their own statistical analyses.New in the Third Edition:Expanded coverage of topics - such as ethical considerations and calculation of power and of sample sizes neededRefers to a wide variety of statistical packages - such as StatXact, Minitab, Testimate, S-plus, Stata, and SPSSIncludes sections on the analysis of angular data, the use of capture-recapture methods, the measurement of agreement between observers, runs tests, and regression diagnostics.
Reviews: 3
Black_Hawk_Down
I haven't read the whole book, but I have other books by Peter Sprent, and they are hard to beat. He has a nice writing style, and gives great examples. You won't be disappointed.
LadyShlak
Nearly all of traditional statistical tests assume that data points are distributed along the "normal," Gaussian bell curve. The assumption may be explicit, may be hidden inside a chi-squared phrase, or may stand silently behind discussions of mean and variance. If your data don't match that assumption, stated or not, the tests give wrong answers.

Nonparametric stats work without that assumption. In fact, most work without !any! assumptions about the distributions of data. These are very robust techniques, and this book demonstrates a number of simple and effective ones. The author describes everything you need to know about a number of tests: when each applies, how to perform it, and how to interpret results. It's a very useful guide for people who need high-quality answers from low-quality data.

Best, many of these procedures are simple enough to apply routinely to almost any data set. I find them helpful for quick checks before applying more detailed kinds of parametric analysis. If your data fail the loose bounds of non-parametric testing, you know that fussier, more high-strung tests have no hope of reasonable answers.

There are no theorems here, and very little development of the underlying principles. That's good for someone who just wants the answers. On the other hand, it's a real weakness if you need to customize analysis for an unusual problem. You just won't find the fundamentals you need for sound improvisation.

//wiredweird

(This review describes the first edition.)
digytal soul
This lame excuse for a textbook was required for my class, but never used. Everyone sold theirs back at the bookstore after the semester. This textbook lacks important items such as an appendix and a lack of detailed analysis of problems. Often, it felt that the book would give questions that it did not explain how to answer in the examples. Not to mention, the definitions are not precise at all. In fact, I could not find a solid definition of "nonparametric" in this book. The only reason why I still have this book is because the bookstore would only give me $2 for it. Looking back now after I got my math degree, I am forced to tap the financial account for a nicer, more descriptive book that is more user-friendly for quicker references. Don't buy this unless it is required for a class. In which case, drop the class.