Product Information
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.Product Identifiers
PublisherTaylor & Francis LTD
ISBN-139780367658021
eBay Product ID (ePID)3046670195
Product Key Features
Number of Pages248 Pages
Publication NameExploratory Multivariate Analysis by Example Using R
LanguageEnglish
SubjectMathematics
Publication Year2020
TypeTextbook
Subject AreaExperimental Psychology
AuthorSebastien Le, Jerome Pages, Francois Husson
Dimensions
Item Height234 mm
Item Weight485 g
Additional Product Features
Country/Region of ManufactureUnited Kingdom
Title_AuthorFrancois Husson, Sebastien Le, Jerome Pages