Factor analysis is the statistical method of describing variability among multiple observed (correlated) variables in terms of a potentially lower number of unobserved variables called factors. This is done by extracting maximum common variance from all variables and putting them into a common score. The driving concept involved here is that multiple observed variables have similar patterns of responses as they are all associated with a latent (i.e., not measured directly) variable.