Volume 6, Issue 12 (December 2019), Pages: 99-104

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 Original Research Paper

 Title: A study of principal components analysis for mixed data

 Author(s): Zakiah I. Kalantan *, Nada A. Alqahtani

 Affiliation(s):

 Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-7040-5623

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2019.12.012

 Abstract:

Analyzing data requires statistical tools to interpret the data information, which helps to improve the process. This is the interpretation of the qualitative and quantitative status of mixed data. The objective of this paper was to study the implementation of principal component analysis on mixed data and explain how to handle this type of databases and to make it possible to extract statistical information over a population under study. The effectiveness of principal component analysis on mixed data was studied using data sets available in the R package and simulated data. 

 © 2019 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Dimension reduction, Mixed data, Principal component analysis, R package

 Article History: Received 18 July 2019, Received in revised form 8 October 2019, Accepted 10 October 2019

 Acknowledgement:

This paper is a component of a Master thesis undertaken by the second author under the supervision of the first author. The authors would like to thank the reviewers for their helpful comments.

 Compliance with ethical standards

 Conflict of interest:  The authors declare that they have no conflict of interest.

 Citation:

 Kalantan ZI and Alqahtani NA (2019). A study of principal components analysis for mixed data. International Journal of Advanced and Applied Sciences, 6(12): 99-104

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 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 

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