Multiple Factor Analysis by Example Using R
Multiple Factor Analysis by Example Using R
Multiple Factor Analysis by Example Using R
Multiple Factor Analysis by Example Using R
Multiple Factor Analysis by Example Using R
Multiple Factor Analysis by Example Using R
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Multiple Factor Analysis by Example Using R

Multiple Factor Analysis by Example Using RAuthor(s): Jrme Pags

Format: Hardback

Publisher: Taylor & Francis Inc, United States

Imprint: Chapman & Hall/CRC

ISBN-13: 9781482205473, 978-1482205473

Synopsis

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).

The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distincti.

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Multiple Factor Analysis by Example Using R

Multiple Factor Analysis by Example Using RAuthor(s): Jrme Pags

Format: Hardback

Publisher: Taylor & Francis Inc, United States

Imprint: Chapman & Hall/CRC

ISBN-13: 9781482205473, 978-1482205473

Synopsis

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).

The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distincti.

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Multiple Factor Analysis by Example Using RAuthor(s): Jrme Pags

Format: Hardback

Publisher: Taylor & Francis Inc, United States

Imprint: Chapman & Hall/CRC

ISBN-13: 9781482205473, 978-1482205473

Synopsis

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).

The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distincti.

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format

hardcover

Language

english

series

chapman and hall/crc the r ser.

type

textbook

Brand

CRC Press

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