file <- "http://www.uvm.edu/~rsingle/stat211/data/extra/Rectangles.txt"
dat<-read.table(file, header=T, na.strings=c("NA",".")) 
 rect.area <- dat$Y
 sample(rect.area,5)

#split the screen
 par(mfrow=c(2,2))

# x is our original (skewed) data 
  x <- rect.area
 #x <- rchisq(2000,3) #uncomment for random skewed data
  hist(x,main="Original Sample")

 n <- 10
 xbar <- vector(length=500)
 for(i in 1:500)
 {
   samp <- sample(x,n,replace=T)
   xbar[i] <- mean(samp)
   cat(i,":",samp,"  xbar=",xbar[i],"\n")
  #print(c(samp,xbar[i]))
 }

 hist(xbar, main="~ Sampling Dist. for Xbar")

#note that the means are approx. equal
 mean(x)
 mean(xbar)

#note the relationship of the SDs of the original and sampling dists
 sd(x)
 sd(x)/sqrt(n)
 sd(xbar)
 
#=====================================
#note that the means are approx. equal
 cat("   mean(x)=", mean(x)   , "\n" )
 cat("mean(xbar)=", mean(xbar), "\n" )

#note the relationship of the SDs of the original and sampling dists
 cat("        sd(x)=", sd(x)        , "\n" )
 cat("sd(x)/sqrt(n)=", sd(x)/sqrt(n), "\n" )
 cat("     sd(xbar)=", sd(xbar)     , "\n" )