Component Matrix - This table contains component loadings, which are the correlations between the variable and the component. Because these are correlations, possible values range from -1 to +1. On the /format subcommand, we used the option blank, which tells SPSS not to print any of the correlations that are .3 or less. This makes the output easier to read by removing the clutter of low correlations that are probably not meaningful anyway. Component - The columns under this heading are the principal components that have been extracted. You usually do not try to interpret the components the way that you would factors that have been extracted from a factor analysis. Rather, most people are interested in the component scores, which are used for data reduction (as opposed to factor analysis where you are looking for underlying latent continua). You can save the component scores to your data set for use in other analyses using the /save subcommand.
http://www.ats.ucla.edu/stat/SPSS/output/principal_components.htm
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