library(boot)
y <- c(33,33,30,34,39,27,32,36,35,42)
y
N = 400
Brep = 10000

# Bootstrap the sample mean
sampmean <- function(y,i) mean(y[i])

bootmean <- boot(data=y,statistic=sampmean,R=Brep)
bootmean
boot.ci(bootmean,conf=.95)
#boot.ci(bootmean,conf=.95,type=c("norm"))
#boot.ci(bootmean,conf=.95,type=c("perc"))
#boot.ci(bootmean,conf=.95,type=c("basic"))
#boot.ci(bootmean,conf=.95,type=c("bca"))
par(mfrow=c(2,1))
hist(bootmean$t,main="Bootstrap Sample Means")
plot(ecdf(bootmean$t),main="Empirical CDF of Bootstrap Means")

# Bootstrap the estimates of the population total
samptotal <- function(y,i) N*mean(y[i])

boottotal <- boot(data=y,statistic=samptotal,R=Brep)
boottotal
boot.ci(boottotal,conf=.95)
#boot.ci(boottotal,conf=.95,type=c("norm"))
#boot.ci(boottotal,conf=.95,type=c("perc"))
#boot.ci(boottotal,conf=.95,type=c("basic"))
#boot.ci(boottotal,conf=.95,type=c("bca"))
par(mfrow=c(2,1))
hist(boottotal$t,main="Bootstrap Population Total Estimates")
plot(ecdf(boottotal$t),main="Empirical CDF of Bootstrap Total Estimates")