Test Planning

To improve test planning for evaluating system reliability, we propose the use of Bayesian methods to incorporate supplementary data and reduce testing duration. Furthermore, we recommend Bayesian methods be employed in the analysis phase to better quantify uncertainty. We find that when using Bayesian Methods for test planning we can scope smaller tests and using Bayesian methods in analysis results in a more precise estimate of reliability – improving uncertainty quantification....

The current fiscal climate demands now, more than ever, that test and evaluation(T&E) provide relevant and credible characterization of system capabilities andshortfalls across all relevant operational conditions as efficiently as possible. Indetermining the answer to the question, “How much testing is enough?” it isimperative that we use a scientifically defensible methodology. Design ofExperiments (DOE) has a proven track record in Operational Test andEvaluation (OT&E) of not only quantifying how much testing is enough, but alsowhere in the operational space the test points should be placed....

Binomial metrics like probability-to-detect or probability-to-hit typically provide operationally meaningful and easy to interpret test outcomes. However, they are information-poor metrics and extremely expensive to test. The standard power calculations to size a test employ hypothesis tests, which typically result in many tens to hundreds of runs. In addition to being expensive, the test is most likely inadequate for characterizing performance over a variety of conditions due to the inherently large statistical uncertainties associated with binomial metrics....

Design of Experiments (DOE) provides a rigorous methodology for developing and evaluating test plans. Design excellence consists of having enough test points placed in the right locations in the operational envelope to answer the questions of interest for the test. The key aspects of a well-designed experiment include: the goal of the test, the response variables, the factors and levels, a method for strategically varying the factors across the operational envelope, and statistical measures of merit....

This presentation is a presentation for the Army Conference on Applied Statistics. The presentation covers a brief introduction to land warfare problems, and devises a methodology using Bayes Theorem to estimate parameters of interest. Two examples are given, a simple one using independent Bernoulli Trials, and a more complex one using correlated Red and Blue casualty data in a Loss Exchange Ratio and a hierarchical model. The presentation demonstrates that the Bayesian approach is successful in both examples at reducing the variance of the estimated parameters, potentially reducing the cost of devising a complex test program....