In This Chapter:
Chapter 8, “Principal Components Analysis,” showed how principal components analysis (PCA) can be used to derive, or extract, underlying and unmeasured components that are expressed overtly in measured variables.
The analysis in Chapter 8 used a small data set, with only three variables and just a few records, to demonstrate the techniques and steps involved in PCA. Excel calculated a correlation matrix from that data set; the matrix was then run through a freeware addin which identified three principal components.
With three original variables, you can’t extract more than three components. If you do extract (and ...