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Books > Social sciences > Psychology > Psychological methodology
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Exploratory Multivariate Analysis by Example Using R (Hardcover, 2nd edition)
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Exploratory Multivariate Analysis by Example Using R (Hardcover, 2nd edition)
Series: Chapman & Hall/CRC Computer Science & Data Analysis
Expected to ship within 10 - 15 working days
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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) and multiple correspondence analysis
(MCA) when variables are categorical, and hierarchical cluster
analysis. The authors take a geometric point of view that provides
a unified vision for exploring multivariate data tables. Within
this framework, they present the principles, indicators, and ways
of representing and visualising objects that are common to the
exploratory methods. The authors show how to use categorical
variables in a PCA context in which variables are quantitative, how
to handle more than two categorical variables in a CA context in
which there are originally two variables, and how to add
quantitative variables in an MCA context in which variables are
categorical. They also illustrate the methods using examples from
various fields, with related R code accessible in the FactoMineR
package developed by the authors.
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