EG 381: Probability Team Projects
Simulation and modeling are very important tools for engineers and scientists. One such technique is called "Monte Carlo" simulation. This is a class of algorithms which obtain numerical results (simulations) by repeated random sampling. This random sampling is done with a random number generator (RNG) (or pseudo-random number since it is not truly random if it is generated by a deterministic process, the generator algorithm). For example repeated calling a (uniform) random number on the interval [0,1] from the RNG and assigning it a value of H for heads if the number is less than or equal to 0.5 or T for tails if it is greater than 0.5 is a Monte Carlo simulation. What this does is divide the interval between [0,1] inclusive into two equal parts and thereby giving us an effective probability of p(H) = 0.5 and p(T) = 0.5. One of the earliest uses of this technique was in simulating the probabilistic chain reaction cascade of the fission of heavy isotopes in the atomic bomb.