Comparison and Empirical Analysis between Principal Component Analysis and Factor Analysis

DOI

10.2991/asshm-13.2013.140How to use a DOI?

Keywords

Principal component analysis; factor analysis; R software; China Statistical Yearbook.

Abstract

We carry out an empirical analysis based on the study of the principal component analysis and the factor analysis, the data is in the 2012 China Statistical Year-book[ ] with 31 provinces and 9 major economic indicators. First by comparing three kinds of methods of factor analysis, we find out that the principal factor anal-ysis method has the minimum sum of squared errors. Then we use the principal component analysis and the principal factor analysis to extract two principal components and two principal factors from the economic indicators. Third, we calculate principal component scores, factor scores, and their comprehensive scores of the provinces under two methods. Finally, we find that the rankings of the provinces under the two methods are different, but the overall trends are consistent, and the trends are also consistent with the actual situations.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

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

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TY  - CONF
AU  - Lu Xu
AU  - Yingying Zhang
PY  - 2013/12
DA  - 2013/12
TI  - Comparison and Empirical Analysis between Principal Component Analysis and Factor Analysis
BT  - Proceedings of the 2013 International Conference on Advances in Social Science, Humanities, and Management
PB  - Atlantis Press
SP  - 749
EP  - 754
SN  - 1951-6851
UR  - https://doi.org/10.2991/asshm-13.2013.140
DO  - 10.2991/asshm-13.2013.140
ID  - Xu2013/12
ER  -