function gaussian
mu1=10;    % mean of the first gaussian
sigma1=3;  % standard deviation
n1 = 20;   % number of examples from the first Gaussian
x1=normrnd(mu1, sigma1, n1, 1); 
% generate 20 random numbers from the above gaussian

mu2=20;   % mean of the second gaussian
sigma2=5;  % standard deviation
n2 = 10;   % number of examples
x2=normrnd(mu2, sigma2, n2, 1); 
% generate 20 random numbers from the above gaussian

compute(x1, x2, n1, n2);

end

function compute(x1, x2, n1, n2)
xbar1 = mean(x1)
sx1 = std(x1)/sqrt(n1)

xbar2 = mean(x2)
sx2 = std(x2)/sqrt(n2)

%decision boundary
dec = (sx1*xbar2 + sx2*xbar1) / (sx1 + sx2)
end