Comparative Study of Principal Components and Factor Analytic Techniques

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Date
2013-10
Authors
Reuben, Benham Zangaluka
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Abstract
Principal component and factor analytic techniques take large number of variables and reduce them to much smaller number of coherent subset such that variables within a subset are related to one another but independent to those in other subsets. These methods summarize patterns of correlation between observed variables. In this research work, Principal Components and Factor Analytic Techniques are compared using data from Nigerian Consumption Pattern 2009/2010. The results revealed that factor analytic techniques preserve correlation more than principal components, while on the other hand, principal components preserve variance more than factor analytic techniques. We therefore conclude that factor analysis should be used when we are interested in making statements about the factors that are responsible for a set of observed responses, and principal component analysis should be used when we are simply interested in performing data reduction.
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A Thesis Report Submitted to the Postgraduate School, Ahmadu Bello University, Zaria in Fulfillment for the Award of M.Sc Degree in Statistics Department of Mathematics
Keywords
Comparative Study,, Principal Components,, Factor of Analytical Techniques,
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