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SOURCES OF VARIABILITY
Pages 13-18

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From page 13...
... Many nonsampling sources of variability are often ignored, because they are not well understood, they are elusive to characterize, or there is little or no information available about them. But only a thorough investigation and presentation of all the associated uncertainties of COLA and of developmental and operational tests will allow decision makers to interpret the results in an informed way (see also the section below on communicating uncertainty to decision makers)
From page 14...
... Defense analysts can provide useful information to decision makers by identifying key factors driving program costs and assessing the sensitivity of cost estimates to plausible changes in these key factors. Kathryn Laskey observed that statistical methods may play an important part in examining the sensitivity of conclusions to assumptions made in the modeling process.
From page 15...
... The Defense Department presumably should be interested in studying sensitivity primarily in order to develop weapon system designs that are robust to deviations from nominal values of operating characteristics. Nair observed that Taguchi's approach to robust design, used primarily to reduce variation in industrial processes, may also be applicable to COLA.
From page 16...
... As defined above, accreditation is a metric-free construct, lacking a commonly accepted measurement scale along which models might be ordered or acceptability thresholds established. The importance and level of effort applied to accreditation will be driven by the analyst's and decision maker's perceived importance of the model's use, and the associated risk will depend on internal model characteristics and on the decision to be informed by the model.
From page 17...
... The assessment and propagation of model uncertainty has received attention in fields outside the defense industry. Dempster alluded to similar efforts in assessing reactor safety within the commercial nuclear energy industry.
From page 18...
... Bayesian methods can also be applied in a straightforward manner to analyze accumulating bodies of data.


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