Multivariate Statistical Methods
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Multivariate Statistical Methods
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Author : Bryan F. J. Manly
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2017-09-30
Multivariate Statistical Methods written by Bryan F. J. Manly and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-30 with categories.
Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Multivariate Statistical Methods
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Author : Marvin Jay Karson
language : en
Publisher: Wiley-Blackwell
Release Date : 1982
Multivariate Statistical Methods written by Marvin Jay Karson and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Mathematics categories.
Multivariate Statistical Methods
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Author : György Terdik
language : en
Publisher: Springer Nature
Release Date : 2021-10-26
Multivariate Statistical Methods written by György Terdik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-26 with Mathematics categories.
This book presents a general method for deriving higher-order statistics of multivariate distributions with simple algorithms that allow for actual calculations. Multivariate nonlinear statistical models require the study of higher-order moments and cumulants. The main tool used for the definitions is the tensor derivative, leading to several useful expressions concerning Hermite polynomials, moments, cumulants, skewness, and kurtosis. A general test of multivariate skewness and kurtosis is obtained from this treatment. Exercises are provided for each chapter to help the readers understand the methods. Lastly, the book includes a comprehensive list of references, equipping readers to explore further on their own.
Advanced And Multivariate Statistical Methods
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Author : Craig A. Mertler
language : en
Publisher: Taylor & Francis
Release Date : 2021-11-29
Advanced And Multivariate Statistical Methods written by Craig A. Mertler and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Psychology categories.
Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate statistical techniques to students who do not necessarily need technical and/or mathematical expertise in these methods. This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The second purpose is to provide students with the skills necessary to interpret research articles that have employed multivariate statistical techniques. Finally, the third purpose of AMSM is to prepare graduate students to apply multivariate statistical methods to the analysis of their own quantitative data or that of their institutions. New to the Seventh Edition All references to SPSS have been updated to Version 27.0 of the software. A brief discussion of practical significance has been added to Chapter 1. New data sets have now been incorporated into the book and are used extensively in the SPSS examples. All the SPSS data sets utilized in this edition are available for download via the companion website. Additional resources on this site include several video tutorials/walk-throughs of the SPSS procedures. These "how-to" videos run approximately 5–10 minutes in length. Advanced and Multivariate Statistical Methods was written for use by students taking a multivariate statistics course as part of a graduate degree program, for example in psychology, education, sociology, criminal justice, social work, mass communication, and nursing.
Multivariate Statistical Methods
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Author : Bryan F.J. Manly
language : en
Publisher: CRC Press
Release Date : 2004-07-06
Multivariate Statistical Methods written by Bryan F.J. Manly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-07-06 with Mathematics categories.
Multivariate methods are now widely used in the quantitative sciences as well as in statistics because of the ready availability of computer packages for performing the calculations. While access to suitable computer software is essential to using multivariate methods, using the software still requires a working knowledge of these methods and how they can be used. Multivariate Statistical Methods: A Primer, Third Edition introduces these methods and provides a general overview of the techniques without overwhelming you with comprehensive details. This thoroughly revised, updated edition of a best-selling introductory text retains the author's trademark clear, concise style but includes a range of new material, new exercises, and supporting materials on the Web. New in the Third Edition: Fully updated references Additional examples and exercises from the social and environmental sciences A comparison of the various statistical software packages, including Stata, Statistica, SAS Minitab, and Genstat, particularly in terms of their ease of use by beginners In his efforts to produce a book that is as short as possible and that enables you to begin to use multivariate methods in an intelligent manner, the author has produced a succinct and handy reference. With updated information on multivariate analyses, new examples using the latest software, and updated references, this book provides a timely introduction to useful tools for statistical analysis.
Methods Of Multivariate Statistics
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Author : Muni S. Srivastava
language : en
Publisher: John Wiley & Sons
Release Date : 2002-07-08
Methods Of Multivariate Statistics written by Muni S. Srivastava 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 2002-07-08 with Mathematics categories.
Get up-to-speed on the latest methods of multivariate statistics Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and "profile analysis," this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include: * Missing at-random observations * "Growth Curve Models" and multivariate one-sided tests applicable in pharmaceutical and medical trials * Bootstrap methods * Principal component method for predicting a multivariate response vector * Outlier detection and handling inference when covariance is singular With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics.
Modern Multivariate Statistical Techniques
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Author : Alan J. Izenman
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-03-02
Modern Multivariate Statistical Techniques written by Alan J. Izenman 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 2009-03-02 with Mathematics categories.
This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.
Multivariate Statistical Methods In Quality Management
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Author : Kai Yang
language : en
Publisher: McGraw Hill Professional
Release Date : 2004-03-17
Multivariate Statistical Methods In Quality Management written by Kai Yang and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-17 with Technology & Engineering categories.
Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods
Advanced And Multivariate Statistical Methods For Social Science Research
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Author : Soleman H. Abu-Bader
language : en
Publisher: Oxford University Press
Release Date : 2010-06
Advanced And Multivariate Statistical Methods For Social Science Research written by Soleman H. Abu-Bader 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 2010-06 with Social Science categories.
Unlike other advanced statistical texts, this book combines the theory and practice behind a number of statistical techniques which students of the social sciences need to evaluate, analyze, and test their research hypotheses. Each chapter discusses the purpose, rationale, and assumptions for using each statistical test, rather than focusing on the memorization of formulas. The tests are further elucidated throughout the text by real examples of analysis. Of particular value to students is the book's detailed discussion of how to utilize SPSS to run each test, read its output, interpret, and write the results. Advanced & Multivariate Statistical Methods for Social Science Research is an indispensable resource for students of disciplines as varied as social work, nursing, public health, psychology, and education. Electronic database files are available for student and instructor use.http: //lyceumbooks.com/StudentResources.htm
Modern Statistical Methods For Spatial And Multivariate Data
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Author : Norou Diawara
language : en
Publisher: Springer
Release Date : 2019-07-11
Modern Statistical Methods For Spatial And Multivariate Data written by Norou Diawara and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Mathematics categories.
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.