Samples from a rolled die

Let's work through generating a simulation using the numpy package. You'll work with the same scenario from the slides, simulating rolls from a standard die numbered 1 through 6, using the randint() function. Take a look at the documentation for this function if you haven't encountered it before.

Starting with a small sample and working your way up to a larger sample, examine the outcome means and come to a conclusion about the underlying theorem.

Generate a sample of 10 die rolls using the randint() function; assign it to our small variable.
Assign the mean of the sample to small_mean and print the results; notice how close it is to the true mean.
Similarly, create a larger sample of 1000 die rolls and assign the list to our large variable.
Assign the mean of the larger sample to large_mean and print the mean; which theorem is at work here?

Exercise

Samples from a rolled die

Instructions