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**Monte Carlo methods ** include all methods that are
r elated to the use of random number. This take account of many well know methods such as Importance Sampling, Bootstrap Sampling, Monte Carlo Simulation, Monte Carlo Integration, Genetic Algorithm, Simulated Annealing, Hasting-Metropolis Algorithm, Percolation, Random walk, Ballistic Deposition, just to name a few of them.

This tutorial will introduce the practical way of **Monte Carlo Simulation**, a subset of Monte Carlo Method. Monte Carlo simulation is one of the most often use method for computer simulations or numerical experiments. It has been applied in wide range of applications from scientific functions such as statistical physics to financial, engineering until military and game.

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What is Monte Carlo Simulation?

What are the advantages of Monte Carlo Simulation?

What are the weaknesses of Monte Carlo Simulation?

Monte Carlo Simulation Nuts and Bolts

Are there any other resources for Monte Carlo Simulation?

Give your comments, questions or suggestions for this tutorial

**See Also**:

Bootstrap sampling tutorial, Machine Learning Algoritm tutorial, Recursive statistics
, Multi Agent simulation

**Preferable reference for this tutorial is**

Teknomo, Kardi. Monte Carlo Simulation Tutorial. http://people.revoledu.com/kardi/tutorial/Simulation