The SPSS Statistics FACTOR procedure provides a comprehensive procedure for doing principal components analysis and factor analysis. The underlying computations for these two techniques are similar, which is why SPSS Statistics bundles them in the same procedure. However, they are sufficiently distinct, so you should consider what your research goals are and choose the appropriate method for your goals.
Principal components analysis (PCA) finds weighted combinations of the original variables that account for the total variance in the original variables. The first principal component finds the linear combination of variables that accounts for as much variance as possible. The second principal component finds the linear combination of variables that accounts for as much of the remaining variance as possible, and also has the property that...
