Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

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.
Complete list of metadatas

Cited literature [40 references]  Display  Hide  Download

https://halshs.archives-ouvertes.fr/halshs-01926339
Contributor : Guillaume Desagulier <>
Submitted on : Monday, February 10, 2020 - 3:41:44 PM
Last modification on : Monday, March 30, 2020 - 9:54:02 PM

File

19_multifactorial_desagulier.p...
Files produced by the author(s)

Licence


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

Identifiers

  • HAL Id : halshs-01926339, version 3

Citation

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

Share

Metrics

Record views

131

Files downloads

504