Principal Components Analysis
Figure 6.1 A Framework for Multivariate Analysis
Principal Component Analysis (PCA) is an exploratory multivariate technique with two overall objectives. One objective is “dimension reduction”— i.e., to turn a collection of, say, 100 variables into a collection of 10 variables that retain almost all the information that was contained in the original 100 variables. The other objective is to discover the structure in the ...