Transcription of 203-30: Principal Component Analysis versus Exploratory ...
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203-30: Principal Component Analysis versus Exploratory ...
1 Paper 203-30 Principal Component Analysis vs. Exploratory Factor Analysis Diana D. Suhr, University of Northern Colorado Abstract Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) are both variable reduction techniques and sometimes mistaken as the same statistical method. However, there are distinct differences between PCA and EFA. Similarities and differences between PCA and EFA will be examined. Examples of PCA and EFA with PRINCOMP and FACTOR will be illustrated and discussed. Introduction You want to run a regression Analysis with the data you ve collected.
2 The total amount of variance in PCA is equal to the number of observed variables being analyzed. In PCA, observed variables are standardized, e.g., mean=0, standard deviation=1, diagonals of …
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