## Sample sizes.
N = c(10,20,40,60)

nrep = 1000 ## Number of simulation replications per sample size value.
nboot = 1000 ## The number of bootstrap data sets.

## Coverage probabilities.
CP = NULL

for (j in 1:length(N))
{
  ## Keep track of how many times the interval covers the true value.
  nc = 0

  n = N[j]

  for (k in 1:nrep)
  {
    ## Simulate a data set.
    X = rnorm(n)

    ## Generate bootstrap data sets from X.
    ii = ceiling(n*runif(n*nboot))
    B = X[ii]
    B = array(B, c(nboot,n))

    ## Get the sample mean for each bootstrap data set.
    M = apply(B, 1, mean)
    M = sort(M)

    ## Get the confidence interval lower and upper bound.
    C = c(M[25], M[975])

    ## Check for coverage.
    if ( (C[1] < 0) & (C[2] > 0) ) { nc = nc+1 }
  }

  CP[j] = nc/nrep
}