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# QAT1 - Ch 15

### Quantitative Analysis - Ch 15

Question | Answer |
---|---|

Simulation | A method for learning about a real system by experimenting with a model that represents the system. |

Simulation experiment | The generation of a sample of values for the probabilistic inputs of a simulation model and computing the resulting values of the model outputs. |

Controllable input | Input to a simulation model that is selected by the decision maker. |

Probabilistic input | Input to a simulation model that is subject to uncertainty. A probabilistic input is described by a probability distribution. |

Risk analysis | The process of predicting the outcome of a decision in the face of uncertainty. |

Parameters | Numerical values that appear in the mathematical relationships of a model. Parameters are considered known and remain constant over all trials of a simulation. |

What-if analysis | A trial-and-error approach to learning about the range of possible outputs for a model. Trial values are chosen for the model inputs (these are the what-ifs) and the value of the output(s) is computed. |

Base-case scenario | Determining the output given the most likely values for the probabilistic inputs of a model. |

Worst-case scenario | Determining the output given the worst values that can be expected for the probabilistic inputs of a model. |

Best-case scenario | Determining the output given the best values that can be expected for the probabilistic inputs of a model. |

Static simulation model | A simulation model used in situations where the state of the system at one point in time does not affect the state of the system at future points in time. Each trial of the simulation is independent. |

Dynamic simulation model | A simulation model used in situations where the state of the system affects how the system changes or evolves over time. |

Event | An instantaneous occurrence that changes the state of the system in a simulation model. |

Discrete-event simulation model | A simulation model that describes how a system evolves over time by using events that occur at discrete points in time. |

Verification | The process of determining that a computer program implements a simulation model as it is intended. |

Validation | The process of determining that a simulation model provides an accurate representation of a real system. |

Created by:
kberna1