Question

What happens in your simulation? Assuming a desired significance level = .05, would reject the null hypothesis based on any these samples? How often would your simulations have led you to reject the null if the significance level were = .10?

Answer 1

A simulation is an approximate imitation of the operation of a process or system that represents its operation over time.

Simulation is used in many contexts, such as simulation of technology for performance optimization, safety engineering, testing, training, education, and video games. Often, computer experiments are used to study simulation models.

Simulation is also used with scientific modelling of natural systems or human systems to gain insight into their functioning, as in economics.

Simulation can be used to show the eventual real effects of alternative conditions and courses of action.

Simulation is also used when the real system cannot be engaged, because it may not be accessible, or it may be dangerous or unacceptable to engage, or it is being designed but not yet built, or it may simply not exist.

Continuous simulation is a simulation where time evolves continuously based on numerical integration of Differential Equations.

Discrete Event Simulation is a simulation where time evolves along events that represent critical moments, while the values of the variables are not relevant between two of them or result trivial to be computed in case of necessity.

Stochastic Simulation is a simulation where some variable or process is regulated by stochastic factors and estimated based on Monte Carlo techniques using pseudo-random numbers, so replicated runs from same boundary conditions are expected to produce different results within a specific confidence band .

Deterministic Simulation is a simulation where the variable is regulated by deterministic algorithms, so replicated runs from the same boundary conditions produce always identical results.

Hybrid Simulation (sometime Combined Simulation) corresponds to a mix between Continuous and Discrete Event Simulation and results in integrating numerically the differential equations between two sequential events to reduce the number of discontinuities.

Distributed Simulation is operating over distributed computers in order to guarantee access from/to different resources (e.g. multi-users operating different systems, or distributed data sets); a classical example is Distributed Interactive Simulation (DIS).

Parallel Simulation is executed over multiple processors usually to distribute the computational workload as it is happening in High-Performance Computing.