ITIS 1P97 Lecture Notes - Lecture 9: Monte Carlo Method, Random Number Table, Cumulative Distribution Function

• School: Brock University
• Department: Information Technology Information Systems
• Course: ITIS 1P97
• Professor: Nigussie Mengesha

Document Summary

Simulation is one of the most widely used quantitative analysis tools. To simulate is to try to duplicate the features, appearance, and characteristics of a real system. Build a mathematical model that comes as close as possible to representing the reality of the system. Physical models can also be built to test systems. The idea behind simulation is to imitate a real world situation mathematically, then to study its properties and operating characteristics, and finally to draw conclusions and make action decisions based on the results of the simulation. Process of simulation: define problem, introduce important variables, construct simulation model, specify values of variables to be tested, conduct the simulation, examine the results, select best course of action. When a system contains elements that exhibit chance in their behaviour, the monte. The basic idea in monte carlo simulation is to generate values for the variables making up the model being studied.