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scientificComputing/simulations/code/normaldata.m

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Matlab

% 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]')