Taking the Next Step: Improving the Science of Test in DoD T and E

Abstract

The current fiscal climate demands now, more than ever, that test and evaluation (T and E) provide relevant and credible characterization of system capabilities and shortfalls across all relevant operational conditions as efficiently as possible. In determining the answer to the question, How much testing is enough? it is imperative that we use a scientifically defensible methodology. Design of Experiments (DOE) has a proven track record in Operational Test and Evaluation (OT and E) of not only quantifying how much testing is enough, but also where in the operational space the test points should be placed. Over the last few years, the T and E community has made great strides in the application of DOE to OT and E, but there is still work to be done in ensuring that the scientific communitys full toolset is utilized. In particular, many test programs have yet to capitalize on the power of the test design when conducting the data analysis. Employing empirical statistical models (e.g., regression techniques, analysis of variance (ANOVA)) allows us to maximize the information from every data point, resulting in defensible analyses that provide crucial information about system performance that decision-makers and warfighters need to know.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2013
Accession Number
AD1123777

Entities

People

  • Laura J. Freeman
  • V. B. Lillard

Organizations

  • Institute for Defense Analyses

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Analysis Of Variance
  • Best Practices
  • Communities
  • Data Analysis
  • Data Mining
  • Data Science
  • Department Of Defense
  • Developmental Tests
  • Education
  • Engineering
  • Experimental Design
  • Governments
  • Guidance
  • Information Science
  • Knowledge Management
  • Mathematics
  • Military Operations
  • Operations Research
  • Probability
  • Regression Analysis
  • Statistical Analysis
  • Statistical Tests
  • Surveys
  • Symposia
  • System Safety
  • Test And Evaluation

Readers

  • Regression Analysis.
  • Systems Analysis and Design

Technology Areas

  • Space