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Simulation is a simple numerical technique for conducting and performing experiments on the computers.Some of the simulation techniques are used in statistics. Monte.Monte Carlo simulation ;This is one of the simulation is used in computer experiment , these experiment involving random sampling for probability distribution.
Simulation techniques are involves in which random sampling from probability and its distributions.There is another type of statistics simulation which is used in formulating the mathematical experiments in which properties of statistical methods is established this type of simulation is called Rationale simulation statistics . This type of statistics evolved exact analytical derivations and large sample approximations .
Some important concepts about Monte Carlo simulation are : Its an estimator which has sampling for true sampling distribution.These sampling distribution has been done under some set of conditions like true distribution of data and finite sample size.
Sometimes derivation of this statistical simulation sampling data distribution is not traceable hence at that time approximate sampling distribution or test statistics are applied under the particular conditions.
Statistical simulation is one of the very important concept of statistics and probability , hence simulation have done in so many different ways. This is the technique of representing the exact statistical calculations.
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