Factor analysis and principal components analysis are different techniques, but they are very similar.

Question

Quizplus · Accepted Answer

Factor analysis and principal components analysis (PCA) are both techniques used for data reduction and structure detection in datasets. However, they have different objectives: PCA aims to maximize variance and transform variables into principal components, while factor analysis seeks to model the underlying structure (latent variables) that explains correlations between observed variables.

Factor Analysis and Principal Components Analysis Are Different Techniques, but They