Mathematical Nonparametric Statistics
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Mathematical Nonparametric Statistics
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Author : Edward B. Manoukian
language : en
Publisher: Taylor & Francis
Release Date : 2022-04-18
Mathematical Nonparametric Statistics written by Edward B. Manoukian and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-18 with Mathematics categories.
First published in 1986. Primarily a reference text, Mathematical Nonparametric Statistics provides mathematicians and students with a systematic mathematical analysis and the fine points of nonparametrical statistical procedures and models used in practice. Divided into five sections and beginning with an extensive chapter on the fundamentals of mathematical statistical methods, its coverage of such topics as the Jackknife method, the Kolmogorov-Smirnov statistic, Box's method and the ch-squared test of fit is rigorous. Written for audiences with differing backgounds in mathematics, the book is of special use to those in the management sciences, industrial engineering, psychology and economics, as well as mathematics.
Mathematical Nonparametric Statistics
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Author : Manoukian
language : en
Publisher: CRC Press
Release Date : 1986-11-10
Mathematical Nonparametric Statistics written by Manoukian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-11-10 with Mathematics categories.
First published in 1986. Primarily a reference text, Mathematical Nonparametric Statistics provides mathematicians and students with a systematic mathematical analysis and the fine points of nonparametrical statistical procedures and models used in practice. Divided into five sections and beginning with an extensive chapter on the fundamentals of mathematical statistical methods, its coverage of such topics as the Jackknife method, the Kolmogorov-Smirnov statistic, Box's method and the ch-squared test of fit is rigorous. Written for audiences with differing backgounds in mathematics, the book is of special use to those in the management sciences, industrial engineering, psychology and economics, as well as mathematics.
Nonparametric Statistics
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Author : Gregory W. Corder
language : en
Publisher: John Wiley & Sons
Release Date : 2014-04-14
Nonparametric Statistics written by Gregory W. Corder and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-14 with Mathematics categories.
“...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." –CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power SPSS® (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures Data sets and odd-numbered solutions provided in an appendix, and tables of critical values Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.
Nonparametric Statistics For Non Statisticians
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Author : Gregory W. Corder
language : en
Publisher: John Wiley & Sons
Release Date : 2009-05-26
Nonparametric Statistics For Non Statisticians written by Gregory W. Corder and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-26 with Mathematics categories.
A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences. Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS® screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to: Test data for normality and randomness Use the Wilcoxon signed rank test to compare two related samples Apply the Mann-Whitney U test to compare two unrelated samples Compare more than two related samples using the Friedman test Employ the Kruskal-Wallis H test to compare more than two unrelated samples Compare variables of ordinal or dichotomous scales Test for nominal scale data A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS®, and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice. Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.
Nonparametric Statistical Methods For Complete And Censored Data
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Author : M.M. Desu
language : en
Publisher: CRC Press
Release Date : 2003-09-29
Nonparametric Statistical Methods For Complete And Censored Data written by M.M. Desu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-29 with Mathematics categories.
Balancing the "cookbook" approach of some texts with the more mathematical approach of others, Nonparametric Statistical Methods for Complete and Censored Data introduces commonly used non-parametric methods for complete data and extends those methods to right censored data analysis. Whenever possible, the authors derive their methodology from the general theory of statistical inference and introduce the concepts intuitively for students with minimal backgrounds. Derivations and mathematical details are relegated to appendices at the end of each chapter, which allows students to easily proceed through each chapter without becoming bogged down in a lot of mathematics. In addition to the nonparametric methods for analyzing complete and censored data, the book covers optimal linear rank statistics, clinical equivalence, analysis of block designs, and precedence tests. To make the material more accessible and practical, the authors use SAS programs to illustrate the various methods included. Exercises in each chapter, SAS code, and a clear, accessible presentation make this an outstanding text for a one-semester senior or graduate-level course in nonparametric statistics for students in a variety of disciplines, from statistics and biostatistics to business, psychology, and the social scientists. Prerequisites: Students will need a solid background in calculus and a two-semester course in mathematical statistics.
Applied Nonparametric Statistics
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Author : Wayne W. Daniel
language : en
Publisher: Wadsworth Publishing Company
Release Date : 1990
Applied Nonparametric Statistics written by Wayne W. Daniel and has been published by Wadsworth Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.
This book covers the most commonly used nonparametric statistical techniques by emphasizing applications rather than theory. Exercises and examples are drawn from various disciplines including agriculture, biology, sociology, education, psychology, medicine, business, geology, and anthropology. The applications of techniques are presented in a step-by-step format that is repeated for all illustrative examples. Concepts are reinforced with many references to statistical literature to show the relevance to real-world problems. Chapters contain references of available computer programs and software packages that apply to methods presented in the book.
Nonparametric Statistics
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Author : Patrice Bertail
language : en
Publisher: Springer
Release Date : 2019-03-08
Nonparametric Statistics written by Patrice Bertail and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-08 with Mathematics categories.
This volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data. The International Society for Nonparametric Statistics is uniquely global, and its international conferences are intended to foster the exchange of ideas and the latest advances among researchers from around the world, in cooperation with established statistical societies such as the Institute of Mathematical Statistics, the Bernoulli Society and the International Statistical Institute. The 3rd ISNPS conference in Avignonattracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge.
An Introduction To Nonparametric Statistics
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Author : John E. Kolassa
language : en
Publisher: CRC Press
Release Date : 2020-09-29
An Introduction To Nonparametric Statistics written by John E. Kolassa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-29 with Mathematics categories.
This textbook presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is payed to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included. Important techniques covered include Rank-based techniques, including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests, are presented. Tests are inverted to produce estimates and confidence intervals. Multivariate tests are explored. Techniques reflecting the dependence of a response variable on explanatory variables are presented. Density estimation is explored. The bootstrap and jackknife are discussed. This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, a course in elementary probability, and a course in regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra.
Nonparametric Statistical Inference
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Author : Jean Dickinson Gibbons
language : en
Publisher: CRC Press
Release Date : 2003-05
Nonparametric Statistical Inference written by Jean Dickinson Gibbons and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05 with Mathematics categories.
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.
Nonparametric Statistics
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Author : Michele La Rocca
language : en
Publisher: Springer Nature
Release Date : 2020-11-11
Nonparametric Statistics written by Michele La Rocca and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-11 with Mathematics categories.
Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.