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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.

Applied Multivariate Statistics with R

2023-01-20 Medical
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Release : 2023-01-20
Genre : Medical
Kind : eBook
Book Rating : 057/5 ( reviews)

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Book Synopsis Applied Multivariate Statistics with R by : Daniel Zelterman

Download or read book Applied Multivariate Statistics with R written by Daniel Zelterman. This book was released on 2023-01-20. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.

An Introduction to Applied Multivariate Analysis

2008-03-10 Business & Economics
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Release : 2008-03-10
Genre : Business & Economics
Kind : eBook
Book Rating : 99X/5 ( reviews)

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Book Synopsis An Introduction to Applied Multivariate Analysis by : Tenko Raykov

Download or read book An Introduction to Applied Multivariate Analysis written by Tenko Raykov. This book was released on 2008-03-10. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies betwe

Exploratory Multivariate Analysis by Example Using R

2017-04-25 Mathematics
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Release : 2017-04-25
Genre : Mathematics
Kind : eBook
Book Rating : 865/5 ( reviews)

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Book Synopsis Exploratory Multivariate Analysis by Example Using R by : Francois Husson

Download or read book Exploratory Multivariate Analysis by Example Using R written by Francois Husson. This book was released on 2017-04-25. Available in PDF, EPUB and Kindle. Book excerpt: Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a

Applied Multivariate Statistical Analysis (Classic Version)

2018-03-18 Multivariate analysis
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Release : 2018-03-18
Genre : Multivariate analysis
Kind : eBook
Book Rating : 397/5 ( reviews)

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Book Synopsis Applied Multivariate Statistical Analysis (Classic Version) by : Richard A. Johnson

Download or read book Applied Multivariate Statistical Analysis (Classic Version) written by Richard A. Johnson. This book was released on 2018-03-18. Available in PDF, EPUB and Kindle. Book excerpt: This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.

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