nsamples = 100;
nresamples = 1000;

% draw a simple random sample ("Stichprobe") from the population:
x = randn(1, nsamples);
fprintf('%-30s  %-5s  %-5s  %-5s\n', '', 'mean', 'stdev', 'sem')
fprintf('%30s  %5.2f  %5.2f  %5.2f\n', 'single SRS', mean(x), std(x), std(x)/sqrt(nsamples))

% bootstrap the mean:
mus = zeros(nresamples,1);    % vector for storing the means
for i = 1:nresamples          % loop for generating the bootstraps
    inx = randi(nsamples, 1, nsamples);  % range, 1D-vector, number
    xr = x(inx);              % resample the original SRS
    mus(i) = mean(xr);        % compute statistic of the resampled SRS
end
fprintf('%30s  %5.2f  %5.2f  -\n', 'bootstrapped distribution', mean(mus), std(mus))

% many SRS (we can do that with the random number generator,
% but not in real life!):
musrs = zeros(nresamples,1);  % vector for the means of each SRS
for i = 1:nresamples
    x = randn(1, nsamples);   % draw a new SRS
    musrs(i) = mean(x);       % compute its mean
end
fprintf('%30s  %5.2f  %5.2f  -\n', 'sampling distribution', mean(musrs), std(musrs))