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A Primer Of Multivariate Statistics

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A Primer Of Multivariate Statistics

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Author : Richard J. Harris
language : en
Publisher: Psychology Press
Release Date : 2001-05-01

A Primer Of Multivariate Statistics written by Richard J. Harris and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-05-01 with Psychology categories.

Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.

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.

A Primer Of Multivariate Statistics

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Author : Richard J. Harris
language : en
Publisher: Psychology Press
Release Date : 2001-05-01

A Primer Of Multivariate Statistics

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Author : Richard J. Harris
language : en
Publisher: Psychology Press
Release Date : 2013-05-03

This text is intended to give students a thorough grounding in multivariate stats, including multiple regression, MANOVA, canonical correlation, factor analysis, and related topics. Previously published by HB/AP.

Multivariate Statistical Methods

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Author : Bryan F.J. Manly
language : en
Publisher: CRC Press
Release Date : 2016-11-03

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 : Jorge A. Navarro
language : en
Publisher: CRC Press
Release Date : 2016-11-03

Multivariate Statistical Methods written by Jorge A. Navarro and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Mathematics categories.

Understanding Multivariate Research

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Author : William Berry
language : en
Publisher: Routledge
Release Date : 2018-05-04

Understanding Multivariate Research written by William Berry and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-04 with Social Science categories.

Although nearly all major social science departments offer graduate students training in quantitative methods, the typical sequencing of topics generally delays training in regression analysis and other multivariate techniques until a student's second year. William Berry and Mitchell Sanders's Understanding Multivariate Research fills this gap with a concise introduction to regression analysis and other multivariate techniques. Their book is designed to give new graduate students a grasp of multivariate analysis sufficient to understand the basic elements of research relying on such analysis that they must read prior to their formal training in quantitative methods. Berry and Sanders effectively cover the techniques seen most commonly in social science journals--regression (including nonlinear and interactive models), logit, probit, and causal models/path analysis. The authors draw on illustrations from across the social sciences, including political science, sociology, marketing and higher education. All topics are developed without relying on the mathematical language of probability theory and statistical inference. Readers are assumed to have no background in descriptive or inferential statistics, and this makes the book highly accessible to students with no prior graduate course work.

Multivariate Statistical Methods A Primer

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Author : Bryan F. Manly
language : en
Publisher: Springer
Release Date : 1986-12-04

Multivariate Statistical Methods A Primer written by Bryan F. Manly and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-12-04 with Juvenile Nonfiction categories.

Methods Of Multivariate Analysis

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Author : Alvin C. Rencher
language : en
Publisher: John Wiley & Sons
Release Date : 2003-04-14

Methods Of Multivariate Analysis written by Alvin C. Rencher 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 2003-04-14 with Mathematics categories.

Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. Multivariate analysis enables researchers to explore the joint performance of such variables and to determine the effect of each variable in the presence of the others. The Second Edition of Alvin Rencher's Methods of Multivariate Analysis provides students of all statistical backgrounds with both the fundamental and more sophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author provides examples and exercises based on fifty-nine real data sets from a wide variety of scientific fields. Rencher takes a "methods" approach to his subject, with an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. The Second Edition contains revised and updated chapters from the critically acclaimed First Edition as well as brand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. Methods of Multivariate Analysis provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.

The Geometry Of Multivariate Statistics

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Author : Thomas D. Wickens
language : en
Publisher: Psychology Press
Release Date : 2014-02-25

The Geometry Of Multivariate Statistics written by Thomas D. Wickens and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-25 with Psychology categories.

A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of optimization on these combinations. Matrix algebra is the vehicle for these calculations. A second approach is computational. Since many users find that they do not need to know the mathematical basis of the techniques as long as they have a way to transform data into results, the computation can be done by a package of computer programs that somebody else has written. An approach from this perspective emphasizes how the computer packages are used, and is usually coupled with rules that allow one to extract the most important numbers from the output and interpret them. Useful as both approaches are--particularly when combined--they can overlook an important aspect of multivariate analysis. To apply it correctly, one needs a way to conceptualize the multivariate relationships that exist among variables. This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.

A Primer Of Multivariate Statistics

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