% getting familiar with the randn() function:
randn(1, 3)
randn(3, 1)
randn(2, 4)

% simulate tiger weights:
mu = 220.0;       % mean and ...
sigma = 40.0;     % ... standard deviation of the tigers in kg
for n = [100, 10000]
    fprintf('\nn=%d:\n', n)
    for i = 1:5
	x = sigma*randn(n, 1) + mu;      % weights of n tigers
        fprintf('  m=%3.0fkg, std=%3.0fkg\n', mean(x), std(x))
    end
end

% plot the data:
plot(x(1:1000), 'o')
xlabel('Index')
ylabel('Weight [kg]')