Modeling and Simulation can be very complex, or it can be a simple part of everyday life.
One can compute the probability of a certain event occurring. As a simple example, the probability of throwing a die and getting a 1 is computed to be 1/6. The Law Of Large Numbers says that if you conduct a trial a large number of times, perhaps an infinite number of times, you will observe the computed probability of that event; it’s an undisputable fact. So, if you are a casino dealing with very large numbers of games, you can compute the simple probability of a casino win for each game, and the casino can be 100% assured, given that they host a very large number of games, that they will win that percentage of times, overall. So, as one might expect, although a player may be gambling, the casino has a sure bet. If a casino offers a bet, they know they will win it, over time. Its all in the numbers.
In the example of throwing the die, we know that once every six rolls, on average, we will roll a 1. Any game of chance, like the roll of die, is essentially a simulation of behavior with a known probability distribution. The goal of data analysts is to create a simple model to determine the behavior of complex systems.
As data analytics becomes increasingly popular, the use of Modeling and Simulation in Systems Engineering is becoming more important too. If you want to learn more about how M&S fits into the Systems Engineering process, ATI has a course that will help you. Consider taking our new offering of Modeling and Simulation in the Systems Engineering Process.
This two-day short course provides an overview of the use of Modeling and Simulation in the Systems Engineering process. After an introduction of key M&S terms and processes, the course presents an overview of the types of models and simulations used across the phases of the Systems Engineering life cycle, from system needs analysis through system sustainment. Examples are given for several types of systems, including systems developed under the U.S. Department of Defense (DoD) acquisition process. The course then provides information on advanced M&S and Digital Engineering topics, including the U.S. DoD Digital Engineering Strategy; the Unified Modeling Language (UML) and the Systems Modeling Language (SysML); interoperable and live-virtual-constructive (LVC) simulation; collaborative environments and asset repositories for Digital Engineering; and modeling the natural and man-made environments.