A self-contained introduction to the theory and methods of non-parametric statistics. Presents a review of probability theory and statistical inference and covers tests based on binomial and multinomial distributions and methods based on ranks and empirical distributions. Includes a thorough collection of statistics tables, hundreds of problems and references, detailed numerical examples for each procedure, and an instant consultant chart to guide the student to the appropriate procedure.
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32 of 32 people found the following review helpful:
5.0 out of 5 stars
excellent update,
By
This review is from: Practical Nonparametric Statistics (Wiley Series in Probability and Statistics) (Paperback)
Since I now have a copy of the third edition I can now say that many of my comments on the second edition still hold. The book is authoritative, clearly written and very much applications oriented. Conover has done a good job of updating it with recent developments. He provides a nice introductory treatment of bootstrap among other things.
28 of 29 people found the following review helpful:
5.0 out of 5 stars
Clear and practical,
By wiredweird "wiredweird" (Earth, or somewhere nearby) - See all my reviews (HALL OF FAME REVIEWER) (TOP 500 REVIEWER)
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This review is from: Practical Nonparametric Statistics (Wiley Series in Probability and Statistics) (Paperback)
Standard statistics make assumptions about how the data are distributed, then give results based on the assumed distribution. Two big problems are that the distribution buried in the analysis may not be the right one, and that the assumption might not even be visible in the analysis. "Nonparametric statistics" (NPS) make no assumptions about the distribution. They work no matter how the data are distributed. Even better, they sometimes work to determine whether the standard techniques have any hope of giving answers.For the practitioner, this book is the broadest catalog I know of how-to for NPS: when each analysis applies and how to apply it. Even more, it gives insight into how some of the tests work. That gives the reader a better chance to understand each technique's strengths, weaknesses, and applicability. For the student, including self-taught, it's a clear and well-organized textbook. The exercises are varied and generally meaningful, and half have answers (though little discussion of how the answers were derived). I wish the book gave more background, including how some of the distributions are derived. Most times, seeing more of the derivation gives me more confidence in using an analysis. Face it, almost every real-life situation needs to be bashed a bit to fit the format expected by a test. Knowing more of the background gives me more assurance that my machinations don't break any important assumptions. Still, it's the author's choice to emphasize practice over theory and I have to respect that. More seriously, I would like to see the bootstrapping section enlarged. Many modern applications, particularly in biology, deal with data so complex that they define analysis or even real understanding. Bootstrapping is just one of many randomization and resampling techniques used for such data. More discussion on the design and analysis of resampling techniques would have been very useful. The book meets its goals, though, and does so admirably. I'm not a stat specialist, but this is the book I'll recommend for heavy users who want a little more than rote recitation of analytic techniques.
14 of 16 people found the following review helpful:
5.0 out of 5 stars
Excellent Introduction,
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This review is from: Practical Nonparametric Statistics (Wiley Series in Probability and Statistics) (Paperback)
This is a very impressive book. All concepts are introduced in an elementary fashion, with derivation following only after an example of the technique. The explanations are lucid and the extensive lists of references very helpful. I would heartily recommend this book to anyone interested in robust estimators and nonparametric methods.
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First Sentence:
One of the attractive qualities of nonparametric statistical methods is that it is not necessary to be an expert in probability theory to understand the theory behind the methods. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
squared ranks test, hypothesized distribution function, chisquared distribution, expected normal scores, critical region corresponds, using normal scores, quantile test, exact quantiles, approximate quantiles, grand median, population distribution function, unknown distribution function, null distribution, monotonic regression, small sample power, selected quantiles, exact tables, true distribution function, pth quantile, median test, fixed marginal totals, population probability distribution, large sample approximation, bivariate random variables, population quantile Key Phrases - Capitalized Phrases (CAPs): (learn more)
Computer Assistance Minitab, Table All, Test Statistic Let, Hypotheses Let, Texas Tech, Totals Row, United States, Computer Assistance Computer, Litter Size, Observation Number, Observation Rank, Outcome Probability, Patient Drug, Unleaded Plus, Use Fisher, Use Kendall, Use Spearman, Men Women, Rank Normal Score Observation Method, Regular Unleaded, Work Exercise New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
One of the attractive qualities of nonparametric statistical methods is that it is not necessary to be an expert in probability theory to understand the theory behind the methods. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
squared ranks test, hypothesized distribution function, chisquared distribution, expected normal scores, critical region corresponds, using normal scores, quantile test, exact quantiles, approximate quantiles, grand median, population distribution function, unknown distribution function, null distribution, monotonic regression, small sample power, selected quantiles, exact tables, true distribution function, pth quantile, median test, fixed marginal totals, population probability distribution, large sample approximation, bivariate random variables, population quantile Key Phrases - Capitalized Phrases (CAPs): (learn more)
Computer Assistance Minitab, Table All, Test Statistic Let, Hypotheses Let, Texas Tech, Totals Row, United States, Computer Assistance Computer, Litter Size, Observation Number, Observation Rank, Outcome Probability, Patient Drug, Unleaded Plus, Use Fisher, Use Kendall, Use Spearman, Men Women, Rank Normal Score Observation Method, Regular Unleaded, Work Exercise New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 100
books:
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100
books
cite this book:
See all 100 books citing this book
- Mathematical Statistics by Steven F. Arnold on 4 pages
- Mathematical Statistics by B. L. Van Der Waerden in Back Matter (1), Back Matter (2), and Back Matter (3)
- Probability Theory and Mathematical Statistics by Marek Fisz in Back Matter (1), and Back Matter (2)
- Introduction to the Theory of Nonparametric Statistics (Wiley Series in Probability and Mathematical Statistics) by Paul R. Thie in Back Matter (1), and Back Matter (2)
- Statistical Methods for Rates and Proportions, 2nd Edition by Joseph L. Fleiss in Back Matter (1), and Back Matter (2)
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- Statistical Methods for Engineers and Scientists (Statistics: A Series of Textbooks and Monographs) by Robert M. Bethea on 5 pages
- Operations Research Analysis in Test and Evaluation (AIAA Education) by Donald L. Giadrosich on page 97, page 144, and Back Matter
- Applied Statistical Designs for the Researcher (Chapman & Hall/CRC Biostatistics Series) by Daryl S. Paulson in Back Matter (1), Back Matter (2), and Back Matter (3)
- Health Research by Catherine Berglund in Back Matter (1), and Back Matter (2)
- Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics) by Reuven Y. Rubinstein in Front Matter, and page 35
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