Factor analysis is a common data reduction technique used in the social
sciences to uncover the latent structure or dimensions of a set of variables.
This presentation will discuss the matrix algebra behind factor analysis. 
We will focus on the process of matrix diagonalization and the role of 
eigenvectors and eigenvalues and their relations to the underlying dimensions.