Factor analysis  From Wikipedia, the free encyclopedia Jump to:
navigation, search  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. For example, it is possible that variations in
four observed variables mainly reflect the variations in two
unobserved variables. Factor analysis searches for such joint
variations in response to unobserved latent variables. The
observed variables are modelled as linear combinations of the
potential factors, plus "error" terms. The information gained
about the interdependencies between observed variables can be
used later to reduce the set of variables in a dataset.
Computationally this technique is equivalent to low-rank
approximation of the matrix of observed variables. Factor
analysis originated in psychometrics and is used in behavioral
sciences, social sciences, marketing, product management,
operations research, and other applied sciences