That very much depends on the PDF. For some distributions, the mean itself is necessary and sufficient (like the exponential), for others the mean and standard deviation are necessary and sufficient (the Gaussian), and for still others the distribution is not parametrized by the mean and std. If this is Gaussian, then I'll assume mu is the mean and sigma the standard deviation.
mu = 10; sigma = 1.5;
x = mu-(4*sigma):0.01:mu+(4*sigma);
y = normpdf(x,mu,sigma);
plot(x,y)
So basically you really need to know which PDF you have the first moment (mean) and second central moment (variance) of.
