Exploratory multivariate analysis by example using R / François Husson, Sébastien Lê, Jérôme Pagès.

By: Husson, François Contributor(s): Lê, Sébastien | Pagès, Jérôme Material type: Text

TextLanguage: English Series: Chapman & Hall/CRC computer science and data analysisPublication details: Boca Raton : CRC Press, c2011. Description: xii, 228 p. : ill. ; 25 cmISBN: 9781439835807 (hardback); 1439835802Subject(s): Multivariate analysis | R (Computer program language)DDC classification: 519.538 LOC classification: QA278 | .H87 2011Online resources: WorldCat details | Ebook Fulltext

Contents:

TOC Principal component analysis (PCA) -- Correspondence analysis (CA) -- Multiple correspondence analysis (MCA) -- Clustering

Summary: Summary: "An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way Read more...

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
E-Book	EWU Library E-book	Non-fiction	519.538 FRE 2011 (Browse shelf(Opens below))		Not for loan
Text	EWU Library Reserve Section	Non-fiction	519.538 FRE 2011 (Browse shelf(Opens below))	C-1	Not For Loan	27413
Text	EWU Library Circulation Section	Non-fiction	519.538 FRE 2011 (Browse shelf(Opens below))	C-2	Available	28175

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Previous	519.536 MES 2012 A second course in statistics :	519.537 SOC 2007 Correlated data analysis :	519.538 FAM 2001 Multivariate statistical modelling based on generalized linear models /	519.538 FRE 2011 Exploratory multivariate analysis by example using R /	519.538 SAA 2000 The analysis of variance :	519.54 GOR 2006 Resampling methods :	519.54 RAM 2012 Multilevel and longitudinal modeling using Stata /	Next

"A Chapman & Hall book".

Includes bibliographical references and index.

TOC Principal component analysis (PCA) --
Correspondence analysis (CA) --
Multiple correspondence analysis (MCA) --
Clustering

Summary:
"An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way Read more...

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