A good way to learn how statistics measure and model a process is to first build an imaginary process, then see how well the statistics see it. Simulation is the word for building an imaginary process; Monte Carlo simulations are simulations done with a random number generator.
Simulations do not have to be complex programs or scripts. As you will see, they can be simple data tables that accrue information repeatedly.