Emulation of the Central Limit Theorem Using a Monte-Carlo Based Approach

Abstract

The majority of simulation experiments fulfill the central limit theorem particularly those that are stochastic and warrant the execution of multiple iterations during the process of their experiment execution. This class of simulation models can benefit from the existence of this theorem by utilizing it as a verification approach that certifies the accuracy in which the simulation experiment has been carried out. This paper formalizes this process and proposes a framework for achieving this given that thus far, the simulation community has not put forward a standard way for doing this. The systematic behaviors of freshmen at a University (particularly related to lectures), were abstracted and studied such that the cycle length for the time that a freshman commits daily towards their lectures was simulated using a Monte-Carlo based approach. The simulation of the academic behavior of freshmen was set up in a fashion that was consistent with the proposed framework so that it was possible to showcase the strategies in which the central limit theorem can be utilized in the verification of a simulation experiment.

Keywords: Simulation Experiment, Monte-Carlo Simulation, Central Limit Theorem