Analysis of Simulation Output

--- Simulation models incorporate random variates and random number generators to mimic real-world stochastic behavior. As a result, the output produced by a simulation is itself random (stochastic) rather than deterministic. This fundamental characteristic...

Simulation output analysis is performed to predict system performance or compare performance of two or more system designs. Since output data from a simulation shows random variability (due to random number generators), two different random number streams p...

In simulation, we rarely observe the true population parameters directly. Instead, we collect output data from simulation runs and use estimation methods to draw conclusions about the system's behavior. Estimation methods are therefore essential tools for i...

In the analysis of simulation output, a confidence interval is needed because: 1. Random Variability in Output: Output data from a simulation shows random variability when random number generators are used. Two different random number streams will produce t...

Definition: Hypothesis testing is a statistical procedure used to make decisions or draw conclusions about a population based on sample data. It involves testing an assumption (hypothesis) about a population parameter. Key Components: Term Description -----...

When a simulation run begins, the system is typically started in an idle state (no entities in service, no entities waiting). This starting condition does not represent the true steady-state behavior of the system, and therefore introduces a systematic erro...

Replication of runs refers to the process of performing multiple independent simulation runs (experiments) of the same model, each using a different random number seed, in order to obtain statistically reliable and unbiased estimates of the system's perform...