For the PCA portion of the seminar, we will introduce topics such as eigenvalues and eigenvectors, communalities, sum of squared loadings, total variance explained, and choosing the number of components to extract. We will begin with variance partitioning and explain how it determines the use of a PCA or EFA model. This seminar will give a practical overview of both principal components analysis (PCA) and exploratory factor analysis (EFA) using SPSS.
