The explorative factor analysis is a procedure of multivariate analysis which aims at identifying structures in large sets of variables. Large sets of variables are often characterized by the fact that as the number of variables increases, it may be assumed that more and more variables are correlated. The exploratory factor analysis aims to structure the relationships in a large set of variables to the extent that it identifies groups of variables that are highly correlated with each other and separates them from less correlated groups. The groups of highly correlated variables are called factors. Apart from the structuring function, factor analysis is also used for data reduction. At the end of the chapter, there is also a brief outlook on confirmatory factor analysis, in which predefined factor structures are examined.