Nonparametric Statistical Methods

Nonparametric Statistical Methods
Author :
Publisher : John Wiley & Sons
Total Pages : 872
Release :
ISBN-10 : 9781118553299
ISBN-13 : 1118553292
Rating : 4/5 (292 Downloads)

Book Synopsis Nonparametric Statistical Methods by : Myles Hollander

Download or read book Nonparametric Statistical Methods written by Myles Hollander and published by John Wiley & Sons. This book was released on 2013-11-25 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Nonparametric Statistical Methods Related Books

Nonparametric Statistical Methods
Language: en
Pages: 872
Authors: Myles Hollander
Categories: Mathematics
Type: BOOK - Published: 2013-11-25 - Publisher: John Wiley & Sons

GET EBOOK

Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly r
Robust Nonparametric Statistical Methods
Language: en
Pages: 492
Authors: Thomas P. Hettmansperger
Categories: Nonparametric statistics
Type: BOOK - Published: 1998 - Publisher: John Wiley & Sons

GET EBOOK

Offering an alternative to traditional statistical procedures which are based on least squares fitting, the authors cover such topics as one and two sample loca
Nonparametric Statistical Methods Using R
Language: en
Pages: 283
Authors: John Kloke
Categories: Mathematics
Type: BOOK - Published: 2014-10-09 - Publisher: CRC Press

GET EBOOK

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and
All of Nonparametric Statistics
Language: en
Pages: 272
Authors: Larry Wasserman
Categories: Mathematics
Type: BOOK - Published: 2006-09-10 - Publisher: Springer Science & Business Media

GET EBOOK

This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at
An Introduction to Nonparametric Statistics
Language: en
Pages: 225
Authors: John E. Kolassa
Categories: Mathematics
Type: BOOK - Published: 2020-09-28 - Publisher: CRC Press

GET EBOOK

An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating