Is Principal Component Analysis and Factor Analysis Applicable to Population and Sample Data?
Principal Component Analysis (PCA) and Factor Analysis are widely utilized multivariate analytical methods capable of being applied to either population-level or sample-level data. The selection between these two applications primarily depends upon the specific objectives of the research and the intrinsic characteristics of the dataset.
When used with population-level data, PCA and Factor Analysis can elucidate underlying structures and relationships representative of the entire population. In contrast, when applied to sample data, these methods identify underlying shared characteristics and patterns within the sampled units. The decision regarding which level of analysis to adopt ultimately hinges upon the particular research aims and the nature of the available data.
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