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What is the difference between factor analysis and principal component analysis?
Principal component analysis and factor analysis are both methods of information concentration, that is, the information of multiple analysis items is concentrated into several general indicators.

On the basis of principal component analysis, factor analysis adds a rotation function to make it easier to name and explain the meaning of factors. If the research focuses on the corresponding relationship between indicators and analysis items, or if you want to name the obtained indicators, SPSSAU suggests using factor analysis.

The purpose of principal component analysis is to concentrate information (but pay little attention to the corresponding relationship between principal component and analysis items), calculate the weight and calculate the comprehensive score. If you want to compare rankings and calculate comprehensive competitiveness, you can use principal component analysis.

SPSSAU can directly use these two methods, and supports automatic saving of factor scores and comprehensive scores without manual calculation.