Nonparametric Methods For Quantitative Analysis

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Nonparametric Methods For Quantitative Analysis

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Author : Jean Dickinson Gibbons
language : en
Publisher: Holt McDougal
Release Date : 1976

Nonparametric Methods For Quantitative Analysis written by Jean Dickinson Gibbons and has been published by Holt McDougal this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Mathematics categories.

Introduction to nonparametric statistics; Goodness-of-fit tests; Inferences concerning location based on one sample or paired samples; Inferences concerning location based on two or more samples; Inferences corcerning scale parameters; General distribution tests for two or more independent samples; Association analysis; Tests for randomness.

Nonparametric Methods For Quantitative Analysis

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Author : Jean Dickinson Gibbons
language : en
Publisher:
Release Date : 1985

Nonparametric Methods For Quantitative Analysis written by Jean Dickinson Gibbons and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Science categories.

Intermediate Statistical Methods For Business And Economics

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Author : Rob Van Den Honert
language : en
Publisher: Juta and Company Ltd
Release Date : 1999

Intermediate Statistical Methods For Business And Economics written by Rob Van Den Honert and has been published by Juta and Company Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Business & Economics categories.

This text is aimed at commerce and social science students who have already completed a first semester course in mathematics and applied statistics.

Nonparametric Regression Methods For Longitudinal Data Analysis

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Author : Hulin Wu
language : en
Publisher: John Wiley & Sons
Release Date : 2006-05-12

Nonparametric Regression Methods For Longitudinal Data Analysis written by Hulin Wu 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 2006-05-12 with Mathematics categories.

Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems.

Nonlinear Time Series

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Author : Jianqing Fan
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-11

Nonlinear Time Series written by Jianqing Fan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-11 with Mathematics categories.

This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

Quantitative Analysis In Archaeology

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Author : Todd L. VanPool
language : en
Publisher: John Wiley & Sons
Release Date : 2011-01-06

Quantitative Analysis In Archaeology written by Todd L. VanPool 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 2011-01-06 with Social Science categories.

Quantitative Analysis in Archaeology introduces the application of quantitative methods in archaeology. It outlines conceptual and statistical principles, illustrates their application, and provides problem sets for practice. Discusses both methodological frameworks and quantitative methods of archaeological analysis Presents statistical material in a clear and straightforward manner ideal for students and professionals in the field Includes illustrative problem sets and practice exercises in each chapter that reinforce practical application of quantitative analysis

Nonparametric Statistics

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Author : Gregory W. Corder
language : en
Publisher: John Wiley & Sons
Release Date : 2014-05-12

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 2014-05-12 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.

The Oxford Handbook Of Quantitative Methods Vol 2 Statistical Analysis

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Author : Todd D. Little
language : en
Publisher: Oxford University Press
Release Date : 2013-02-01

The Oxford Handbook Of Quantitative Methods Vol 2 Statistical Analysis written by Todd D. Little and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-01 with Psychology categories.

Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.

Introduction To Nonparametric Statistics For The Biological Sciences Using R

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Author : Thomas W. MacFarland
language : en
Publisher: Springer
Release Date : 2016-07-06

Introduction To Nonparametric Statistics For The Biological Sciences Using R written by Thomas W. MacFarland and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-06 with Medical categories.

This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.

A Conceptual Guide To Statistics Using Spss

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Author : Elliot T. Berkman
language : en
Publisher: SAGE
Release Date : 2012

A Conceptual Guide To Statistics Using Spss written by Elliot T. Berkman and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.

This book helps students develop a conceptual understanding of a variety of statistical tests by linking the statistics with the computational steps and output from SPSS. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. For example, seeing exactly how the concept of variance is used in SPSS-how it is converted into a number based on real data, which other concepts it is associated with, and where it appears in various statistical tests-will not only help students understand how to use statistical tests in SPSS and how to interpret their output, but will also teach them about the concept of variance itself. Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, pointing out wherever possible how the SPSS procedure and output connects back to the conceptual underpinnings of the test. Each of the steps is accompanied by annotated screen shots from SPSS, and relevant components of output are highlighted in both the text and in the figures. Sections explain the conceptual machinery underlying the statistical tests. In contrast to merely presenting the equations for computing the statistic, these sections describe the idea behind each test in plain language and help students make the connection between the ideas and SPSS procedures. These include extensive treatment of custom hypothesis testing in ANOVA, MANOVA, ANCOVA, and regression, and an entire chapter on the advanced matrix algebra functions available only through syntax in SPSS. The book will be appropriate for both advanced undergraduate and graduate level courses in statistics.