Exploratory research on a topic may identify many variables of possible interest, so many that their sheer number can become a hindrance to effective and efficient analysis.
Factor analysis is a “data reduction” technique that reduce the number of variables studied to a more limited number of underlying “factors.”
Factor analysis is based on a model that supposes that correlations between pairs of measured variables can be explained by the connections of the measured variables to a small number of non-measurable (latent), but meaningful variables, which are termed factors.
The aims of factor analysis are to: (i) identify the number of factors; (ii) define the factors as functions of the measured variables; (iii) study the factors which have been defined.