Factor analysis is a technique for condensing a large number of variables into a smaller number of factors. This method extracts the maximum common variance from all variables and converts it into a single score. This score can be used for further analysis as an index of all variables. Factor analysis is a subset of the general linear model (GLM). It also makes several assumptions, including the existence of a linear relationship, the absence of multicollinearity, the inclusion of relevant variables in the analysis, and the presence of a true correlation between variables and factors. Several methods are available, but the principal component analysis is the most widely used.