Hi, Thanks so much for the reply. I could go furthur in this problem. And here is the following issue: In my understanding, the continues calls to random.multivariate_normal would get a serials of random vairables which are all following the joint normal distribution. Then what about how to reset the random generating in each iteration? Assuming that I have to simulate something for 50 iterations then to get the average value. In each iteration I need a serial of random pairs which follows the joint normal distrubition. The interations are expected to be independent to each other. Thus: In iteration 1: serial = [] in sub loop serial.append(random.multivariate_normal(m, cov)) ... And in iteration 2, I want a fresh serial which should not be affected by the previous one s. Is there any problem to empty the serial then still call random.multivariate_normal(m, cov) ? In my understanding if there is no refresh or something performed to the internal random generator, the random.multivariate_normal would continue to generate variables in the context of the previous ones. Br, Parvel