Is Monte Carlo Simulation the same as just conducting experiment several times and then averaging results? Why is it then called like that?
Monte Carlo method (there is also Monte Carlo algorithm) is a general name for a broad class of algorithms that use random sampling to obtain numerical results. It is used to solve statistical problems by simulation. It was one of the first methods of computer simulation that was described (see here for broader introduction and references). In plain English, Monte Carlo is drawing random numbers to simulate something and afterwards some kind of aggregation is often used to make conclusions about the simulated phenomenon.
It was that time I suggested an obvious name for statistical method - a suggestion not unrelated to the fact that Stan [Ulam] had an uncle who would borrow money from the relatives because he "just had to go to Monte Carlo".
Metropolis, N. (1987). The Beginning of Monte Carlo Method. Los Alamos Science, 125-130.
Anderson, H.L. (1986). Metropolis, Monte Carlo, and MANIAC. Los Alamos Science, 96-108.
A repeated experiment is a good start .
In finance, for example, we try to plan for a 30 year retirement, with investment returns that are not guaranteed. One model states that each year has a 10% return with 14% standard deviation. Monte Carlo can help us understand the expected return by treating this return as a random event and running the 30 year return some 1000+ times.