In this chapter, we will cover the following recipes:
Finding the principal components of a set of data
Using factor analysis to identify the underlying factors
Analyzing the consistency of a test paper using item analysis
Finding similarity in results by rows using cluster observations
Finding similarity across columns using cluster variables
Identifying groups in data using cluster K-means
The discriminant analysis
Analyzing two-way contingency tables with a simple correspondence analysis
Studying complex contingency tables with a multiple correspondence analysis