The Importance of M and S in Operational Testing and the Need for Rigorous Validation

Abstract

Modeling and simulation (M and S) is often an important element of operational evaluations of effectiveness, suitability, survivability, and lethality. In order to have an adequate understanding of, and confidence in, the results obtained from M and S, statistically rigorous techniques should be applied to the validation process wherever possible. Design of experiments methodologies should be employed to determine what live and simulation data are needed to support rigorous validation, and formal statistical tests should be used to compare live and simulated data. This briefing discusses the importance of M and S in operational testing through a few examples, provides an overview of the existing Director, Operational Test and Evaluation (DOT and E) guidance on M and S validation, and outlines several statistically rigorous techniques for validation. All data and graphical representations in the brief are notional, and the methodologies presented are certainly exhaustive. No specific solution is endorsed; rather, the briefing aims to highlight the type of statistical thinking that should be applied before accrediting M and S capabilities for use in OT.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2016
Accession Number
AD1123396

Entities

People

  • Kelly Mcginnity

Organizations

  • Institute for Defense Analyses

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Computer Programming
  • Computer Simulations
  • Computers
  • Data Science
  • Experimental Design
  • Field Tests
  • Flight
  • Flight Paths
  • Gaussian Processes
  • Geometry
  • Guidance
  • Guided Weapons
  • Information Science
  • Military Acquisition
  • Probability
  • Reliability
  • Ships
  • Simulations
  • Statistical Analysis
  • Statistical Tests
  • Stochastic Processes
  • Test And Evaluation
  • Test Facilities
  • Validation

Readers

  • Aerospace Test and Evaluation
  • Distributed Systems and Data Platform Development
  • Life Cycle Cost Analysis