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Methodological Analysis of Principal Component Analysis ...

IJCEM International Journal of Computational Engineering & Management, Vol. 16 Issue 2, March 2013 ISSN (Online): 2230-7893 IJCEM 32 Methodological Analysis of Principal Component Analysis (PCA) Method Liton Chandra Paul1, Abdulla Al Suman2, Nahid Sultan3 1,2,3 Department of Electronics & Telecommunication Engineering, Rajshahi University of Engineering & Technology, Rajshahi-6204, Bangladesh. Abstract Principal Components Analysis (PCA) is a practical and standard statistical tool in modern data Analysis that has found application in different areas such as face recognition, image compression and neuroscience. It has been called one of the most precious results from applied linear algebra. PCA is a straightforward, non-parametric method for extracting pertinent information from confusing data sets.

Principal component analysis is simply a variable reduction procedure that (typically) results in a relatively small number of components that account for most of the variance in a set of observed variables [3]. In summary, both factor analysis and principal component analysis have important roles to play in social science

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