Factor analysis is a method for condensing a large number of variables into a smaller number of factors. This method takes the largest common variance from all variables and converts it to a single score. We can use this score as an index of all variables for further investigation. Factor analysis is a subset of the general linear model (GLM), and it makes certain assumptions: there is a linear relationship, no multicollinearity, relevant variables are included in the analysis, and there is real correlation between variables and factors. There are other ways to choose from, but principal component analysis is the most popular.