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Multivariate Exploratory Approaches

Abstract : This chapter provides both a theoretical discussion of what multivariate exploratory approaches entail and step-by-step instructions to implement each of them with R. Four methods are presented: correspondence analysis, multiple correspondence analysis, principal component analysis, and exploratory factor analysis. These methods are designed to explore and summarize large and complex data tables by means of summary statistics. They help generate hypotheses by providing informative clusters using the variable values that characterize each observation.
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Contributor : Guillaume Desagulier Connect in order to contact the contributor
Submitted on : Monday, February 10, 2020 - 3:41:44 PM
Last modification on : Wednesday, November 3, 2021 - 9:49:50 AM


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Distributed under a Creative Commons Attribution - NonCommercial - ShareAlike 4.0 International License


  • HAL Id : halshs-01926339, version 3


Guillaume Desagulier. Multivariate Exploratory Approaches. 2020. ⟨halshs-01926339v3⟩



Les métriques sont temporairement indisponibles