Principios de Estadística No Paramétrica
Principios de Estadística No Paramétrica

Author: Mario Miguel Ojeda

Publisher: Editorial Academica Espanola

Published: 2013

Total Pages: 216

ISBN-13: 9783659041341

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Este libro ha sido escrito con el propósito de constituirse tanto en un medio para diseñar y conducir cursos introductorios de estadística no paramétrica, como para servir de fuente de consulta de quienes apliquen o investiguen sobre los métodos no paramétricos. Su conformación actual responde a una amplia gama de necesidades educativas con respecto de esta temática, aunque de la misma manera, tiene un carácter de iniciación a la disciplina. Puede ser la base de un curso de estadística no paramétrica para estadísticos, o para estudiantes de posgrado de otras áreas. Además, puede ocuparse como apoyo para seminarios y talleres de corta duración, en eventos como coloquios y congresos, donde se plantee cubrir temas muy concretos de estadística no paramétrica. Esto es posible dado que la lista de temas que se presenta constituye la suma de los temas convencionales, pero también incluye los aspectos teóricos y metodológicos, y algunos temas poco convencionales.

Nonparametric Statistics
Nonparametric Statistics

Author: Jean Dickinson Gibbons

Publisher: SAGE

Published: 1993

Total Pages: 98

ISBN-13: 9780803939516

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Through the use of actual research investigations that have appeared in recent social science journals, Gibbons shows the reader the specific methodology and logical rationale for many of the best-known and most frequently used nonparametric methods that are applicable to most small and large sample sizes. The methods are organized according to the type of sample structure that produced the data to be analyzed, and the inference types covered are limited to location tests, such as the sign test, the Mann-Whitney-Wilcoxon test, the Kruskal-Wallis test and Friedman's test. The formal introduction of each test is followed by a data example, calculated first by hand and then by computer.

Nonparametric Statistical Methods For Complete and Censored Data
Nonparametric Statistical Methods For Complete and Censored Data

Author: M.M. Desu

Publisher: CRC Press

Published: 2003-09-29

Total Pages: 392

ISBN-13: 9781584883197

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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 Statistical Methods
Applied Nonparametric Statistical Methods

Author: Peter Sprent

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 536

ISBN-13: 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

Published: 2012-12-06

Total Pages: 268

ISBN-13: 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.

A Parametric Approach to Nonparametric Statistics
A Parametric Approach to Nonparametric Statistics

Author: Mayer Alvo

Publisher: Springer

Published: 2018-10-12

Total Pages: 277

ISBN-13: 3319941534

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This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter. This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.

Nonparametric Statistical Inference
Nonparametric Statistical Inference

Author: Jean Dickinson Gibbons

Publisher: CRC Press

Published: 2014-03-10

Total Pages: 350

ISBN-13: 113553201X

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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.