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dc.contributor.advisorMoses, O. Douglas
dc.contributor.advisorLiao, Shu S.
dc.contributor.authorTagg, David A.
dc.dateDecember 1992
dc.date.accessioned2012-11-29T16:18:07Z
dc.date.available2012-11-29T16:18:07Z
dc.date.issued1992-12
dc.identifier.urihttp://hdl.handle.net/10945/23881
dc.description.abstractThis study evaluates the quality of cost estimates produced by each of four cost progress models--a random walk model, the traditional learning curve model, a production rate model (fixed-variable model), and a model incorporating both learning curve and production rate effects (Bemis production rate adjustment model). Emphasis is on assessing the level of bias associated with these models and determining the influence of various factors on model performance. Findings indicate, on average, the learning curve and Bemis models underestimate unit costs, while the random walk and fixed-variable models overestimate unit costs. Different factors are evaluated to determine their significance in explaining variations in the bias of their significance in explaining variations in the bias of unit cost predictions and relationships between the significant variables and model cost prediction bias are described Findings indicate the Bemis model is superior to the other cost progress models because it exhibits the least bias and is not significantly influenced (in terms of bias) by variations in the factors considered.en_US
dc.description.urihttp://archive.org/details/evaluatingbiasof1094523881
dc.format.extent103 p.en_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleEvaluating the bias of alternative cost progress models: tests using aerospace industry acquisition programsen_US
dc.typeThesisen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentDepartment of Administrative Sciences
dc.subject.authorCost progress modelsen_US
dc.subject.authorCost estimation modelsen_US
dc.subject.authorCost prediction modelsen_US
dc.subject.authorProgress functionsen_US
dc.subject.authorProduction rate adjustment modelen_US
dc.subject.authorLearning curve modelen_US
dc.subject.authorRandom walk modelen_US
dc.subject.authorBemis modelen_US
dc.subject.authorEvaluating model biasen_US
dc.subject.authorCost production biasen_US
dc.subject.authorCost estimation biasen_US
dc.description.serviceCaptain, United States Marine Corpsen_US
etd.thesisdegree.nameM.S. in Managementen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineManagementen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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