If in a factor analytic analysis two variables, X1 and X2, are significantly correlated, we then infer that?
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Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors
So, if 2 variables are significantly correlated, like in our case X1 and X2 are , then we can designate a single vector or a factor which captures most of the variations in these 2 variables.
We no longer 2 vectors/factors then. This essentially decreases the number of dimensions in our dataset.
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