#read in the data
#National Track Records for Women: 100, 200, 400, 800, 1500, 3000 m, marathon
#in s,s,s,min,min,min,min
#Men records are in T8-6.DAT, after 1500 there is 5000, 10,000 and no 3000 m
ntrw <- read.table("http://www.rohan.sdsu.edu/~babailey/reut09/T1-9.DAT", 
row.names=8, header=F)

#look at 1st 5 rows of data
ntrw[1:5,]

#examine correlation matrix
cor(ntrw)

#PCA Analysis with standardized data (unit variance), center=T is default)
pcaw <- prcomp(ntrw, scale=T)
summary(pcaw)
pcaw

#scree plot to determine # of PC's needed 
plot(pcaw, type="lines")
#or
screeplot(pcaw, type="lines")

#Biplot for helping in interpretation
biplot(pcaw)

#rank countries based on 1st PC (faster is better?)
sort(pcaw$x[,1])