sampling from a normal distribution

I usually generate a sample from a normal distribution N(mu,sigmasq) (where mu is the mean and sigmasq is the variance) as follows (assume a 1D case)

 mu=1.5;
 sigmasq=0.01;
 p = mu+chol(sigmasq)*randn;

or

 p = mvnrnd(mu,sigmasq);

I now want to generate a sample from N(mu,k^2, sigmasq) with k=10. One way is

 p = mvnrnd(mu,k^2*sigmasq);

Which among the two below statements is correct?

 p = mu + chol(k^2*sigmasq)*randn;
 p = mu + k^2*chol(sigmasq)*randn;