What is Monte Carlo Simulation (MCS)

Consider an algorithm, say for recruitment; feed random samples of potential subjects into it to determine its variability. MCS predicts outcomes of worst and best cases plus those in between ( Metropolis & Ulam, 1949 ). It is a parametric model ( y = f(x 1 , x 2 , … x n ) , with variables (x 1 , x 2 , … x n ) ) unlike ordinary equations because it accounts for changes in the variables. It produces lots of results with random numbers for variable inputs. This allows MCS to show distributions that might indicate risk. With this iterative technique to determine statistical properties, graphs of probability distributions can be made, interdependent relationships can be analyzed, and multiple effects of the changes in variables can be simulated.

Recruitment Portfolio Games

James Grayson (Georgia Regents University, USA), LeeAnn Kung (Auburn University, USA), and William F. Lawless (Paine College, USA)