#Data from table 1, page 188

> x<-c(44.4,45.9,41.9,53.3,44.7,44.1,50.7,45.2,60.1)

> y<-c(2.6,3.1,2.5,5.0,3.6,4.0,5.2,2.8,3.8)

> rtoz<-function(r,rho,n){

O<-.5*log((1+r)/(1-r))

E<-.5*log((1+rho)/(1-rho))

Var<-1/(n-3)

return((O-E)/sqrt(Var))}

> cor.test(x,y,method="pearson")

Pearson's product-moment correlation

data: x and y

t = 1.8411, df = 7, p-value = 0.1082

alternative hypothesis: true coef is not equal to 0

sample estimates:

cor

0.5711815

> cor.test(x,y,method="kendall")

Kendall's rank correlation tau

data: x and y

normal-z = 1.6681, p-value = 0.0953

alternative hypothesis: true tau is not equal to 0

sample estimates:

tau

0.4444444