Practical statistical analysis of simulation output data: the state of the art

  • Authors:
  • Averill M. Law

  • Affiliations:
  • The University of Arizona, Tucson, Arizona

  • Venue:
  • WSC '82 Proceedings of the 14th conference on Winter Simulation - Volume 2
  • Year:
  • 1982

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Abstract

It has been our observation that in many simulation studies a large amount of time and money is spent on model development and programming, but little effort is made to analyze the simulation output data in an appropriate manner. As a matter of fact, a common mode of operation is to make a single simulation run of somewhat arbitrary length and then treat the resulting simulation estimates as being the "true" answers for the model. Since these estimates are observations of random variables which may have large variances, these estimates may, in a particular simulation run, differ greatly from the corresponding true answers. The net effect is, of course, that there may be a significant probability of making erroneous inferences about the system under study.