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Applied Nonparametric Statistical Methods

Applied Nonparametric Statistical Methods
Author: Peter Sprent
Publisher: CRC Press
Total Pages: 536
Release: 2016-04-19
Genre: Mathematics
ISBN: 1439894019

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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


Applied Nonparametric Statistical Methods

Applied Nonparametric Statistical Methods
Author: Peter Sprent
Publisher: Springer Science & Business Media
Total Pages: 268
Release: 2012-12-06
Genre: Science
ISBN: 9400912234

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This book is a practical introduction to statistical techniques called nonpara metric methods. Using examples, we explain assumptions and demonstrate procedures; theory is kept to a minimum. We show how basic problems are tackled and try to clear up common misapprehensions so as to help both students of statistics meeting the methods for the first time and workers in other fields faced with data needing simple but informative analysis. An analogy between experimenters and car drivers describes our aim. Statistical analyses may be done by following a set of rules without understanding their logical basis, but this has dangers. It is like driving a car with no inkling ofhow the internal combustion engine, the gears, the ignition system, the brakes actually work. Understanding the rudiments helps one get better performance and makesdrivingsafer;appropriate gearchanges become a way to reduce engine stress, prolong engine life, improve fuel economy, minimize wear on brake linings. Knowing how to change the engine oil or replace worn sparking plugs is notessential for adriver, but it will reduce costs. Learning such basics will not make one a fully fledged mechanic, even less an automotive engineer; but it all contributes to more economical and safer driving, alertingone to the dangers ofbald tyres, aleakingexhaust, worn brake linings.


Applied Nonparametric Statistical Methods, Third Edition

Applied Nonparametric Statistical Methods, Third Edition
Author: Peter Sprent
Publisher: Chapman and Hall/CRC
Total Pages: 480
Release: 2000-09-07
Genre: Mathematics
ISBN: 9781584881452

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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 needed Refers to a wide variety of statistical packages - such as StatXact, Minitab, Testimate, S-plus, Stata, and SPSS Includes sections on the analysis of angular data, the use of capture-recapture methods, the measurement of agreement between observers, runs tests, and regression diagnostics.


Nonparametric Statistical Methods

Nonparametric Statistical Methods
Author: Myles Hollander
Publisher: John Wiley & Sons
Total Pages: 978
Release: 2013-11-25
Genre: Mathematics
ISBN: 1118553292

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Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.


Robust Nonparametric Statistical Methods

Robust Nonparametric Statistical Methods
Author: Thomas P. Hettmansperger
Publisher: John Wiley & Sons
Total Pages: 492
Release: 1998
Genre: Nonparametric statistics
ISBN:

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Offering an alternative to traditional statistical procedures which are based on least squares fitting, the authors cover such topics as one and two sample location models, linear models, and multivariate models. Both theory and applications are examined.


Nonparametric Statistical Inference, Fourth Edition

Nonparametric Statistical Inference, Fourth Edition
Author: Jean Dickinson Gibbons
Publisher: CRC Press
Total Pages: 680
Release: 2003-05-09
Genre: Mathematics
ISBN: 9780824740528

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Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.


Statistical Methods

Statistical Methods
Author: Rudolf J. Freund
Publisher: Elsevier
Total Pages: 694
Release: 2003-01-07
Genre: Mathematics
ISBN: 0080498221

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This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters


Applied Non-Parametric Statistical Methods, Second Edition

Applied Non-Parametric Statistical Methods, Second Edition
Author: Peter Sprent
Publisher: Chapman and Hall/CRC
Total Pages: 356
Release: 1993
Genre: Mathematics
ISBN:

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This introduction to nonparametric methods, now in its second edition, highlights the way modern computer software enables one to carry out exact tests based on permutation distributions where one had previously to resort to asymptotic results.


Nonparametric Statistical Methods Using R

Nonparametric Statistical Methods Using R
Author: John Kloke
Publisher: CRC Press
Total Pages: 291
Release: 2014-10-09
Genre: Mathematics
ISBN: 1439873437

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A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.