do monte carlo simulation with correlation in matlab

main.m
% means and standard deviations of x and y
mu_x = 5;
sigma_x = 1;
mu_y = 10;
sigma_y = 2;
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main.m
% generate 1000 random samples for x and y
n = 1000;
x_samples = normrnd(mu_x, sigma_x, n, 1);
y_samples = normrnd(mu_y, sigma_y, n, 1);
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main.m
% correlation matrix
corr_xy = 0.7;
corr_matrix = [1 corr_xy; corr_xy 1];
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main.m
% generate correlated random variables using mvnrnd function
correlated_samples = mvnrnd([mu_x mu_y], [sigma_x^2 corr_xy*sigma_x*sigma_y; corr_xy*sigma_x*sigma_y sigma_y^2], n);
x_samples = correlated_samples(:,1);
y_samples = correlated_samples(:,2);
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main.m
% repeat simulation 100 times
num_simulations = 100;
z_samples = zeros(n,num_simulations);
for i = 1:num_simulations
    % generate correlated random variables using mvnrnd function
    correlated_samples = mvnrnd([mu_x mu_y], [sigma_x^2 corr_xy*sigma_x*sigma_y; corr_xy*sigma_x*sigma_y sigma_y^2], n);
    x_samples = correlated_samples(:,1);
    y_samples = correlated_samples(:,2);
    % calculate z as a function of x and y
    z_samples(:,i) = 2*x_samples - 3*y_samples;
end
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main.m
% plot histogram of z_samples
histogram(z_samples)
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