# 3) Problem 3.5 from the textbook asks you to do and interpret
a principal components analysis on the given correlation matrix,
which can be entered into R with the following code:
my.cor.mat <- matrix(c(1,.402,.396,.301,.305,.339,.340,
.402,1,.618,.150,.135,.206,.183, .396,.618,1,.321,.289,.363,.345,
.301,.150,.321,1,.846,.759,.661, .305,.135,.289,.846,1,.797,.800,
.339,.206,.363,.759,.797,1,.736, .340,.183,.345,.661,.800,.736,1),
ncol=7, nrow=7, byrow=T);
As mentioned in the book, the 7 variables are 'head length',
'head breadth', 'face breadth', 'left finger length', 'left forearm
length', 'left foot length','height'.
Obtain the principal components (including choosing an
appropriate number of PCs). Also...