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Multivariate Statistical Analysis

2008-11-25 Mathematics
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Release : 2008-11-25
Genre : Mathematics
Kind : eBook
Book Rating : 111/5 ( reviews)

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Book Synopsis Multivariate Statistical Analysis by : Mukhopadhyay Parimal

Download or read book Multivariate Statistical Analysis written by Mukhopadhyay Parimal. This book was released on 2008-11-25. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each. With its roots in matrix algebra, for which a separate chapter has been added as an appendix, the book includes both data-oriented techniques and a reasonable coverage of classical methods supplemented by comments about robustness and general practical applicability. It also illustrates the methods of numerical calculations at various stages.This self-contained book is ideal as an advanced textbook for graduate students in statistics and other disciplines like social, biological and physical sciences. It will also be of benefit to professional statisticians.The author is a former Professor of the Indian Statistical Institute, India.

Introduction to Multivariate Statistical Analysis in Chemometrics

2016-04-19 Mathematics
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Release : 2016-04-19
Genre : Mathematics
Kind : eBook
Book Rating : 491/5 ( reviews)

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Book Synopsis Introduction to Multivariate Statistical Analysis in Chemometrics by : Kurt Varmuza

Download or read book Introduction to Multivariate Statistical Analysis in Chemometrics written by Kurt Varmuza. This book was released on 2016-04-19. Available in PDF, EPUB and Kindle. Book excerpt: Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical Analysis in Chemometrics presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. It includes discussions of various statistical methods, such as

An Introduction to Multivariate Statistical Analysis

2003-07-25 Business & Economics
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Release : 2003-07-25
Genre : Business & Economics
Kind : eBook
Book Rating : 919/5 ( reviews)

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Book Synopsis An Introduction to Multivariate Statistical Analysis by : T. W. Anderson

Download or read book An Introduction to Multivariate Statistical Analysis written by T. W. Anderson. This book was released on 2003-07-25. Available in PDF, EPUB and Kindle. Book excerpt: Perfected over three editions and more than forty years, this field- and classroom-tested reference: * Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. * Treats all the basic and important topics in multivariate statistics. * Adds two new chapters, along with a number of new sections. * Provides the most methodical, up-to-date information on MV statistics available.

Multivariate Statistical Methods

2016-11-03 Mathematics
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Release : 2016-11-03
Genre : Mathematics
Kind : eBook
Book Rating : 995/5 ( reviews)

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Book Synopsis Multivariate Statistical Methods by : Bryan F.J. Manly

Download or read book Multivariate Statistical Methods written by Bryan F.J. Manly. This book was released on 2016-11-03. Available in PDF, EPUB and Kindle. Book excerpt: 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.

An Introduction to Applied Multivariate Analysis with R

2011-04-23 Mathematics
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Release : 2011-04-23
Genre : Mathematics
Kind : eBook
Book Rating : 508/5 ( reviews)

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Book Synopsis An Introduction to Applied Multivariate Analysis with R by : Brian Everitt

Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt. This book was released on 2011-04-23. Available in PDF, EPUB and Kindle. Book excerpt: The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

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