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Description
The purpose of this thesis is to develop a model to forecast civilian personnel inventory for the National Security Agency (NSA). Accurate prediction of personnel inventories will help the NSA with issues ranging from hiring, promotion, and ethnic/gender diversity to the development of cost-effective force reduction programs. The model must be capable of producing multiple-year forecasts of the NSA's civilian force structure with a minimum fidelity level that allows for break-out by years-of service, career field, and grade. Historical data will be utilized to estimate logistic regression parameters that will compose the internal workings of the model. The JMP statistical software package will be used for data analysis, while the model will be developed as a Microsoft Excel application.
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The purpose of this thesis is to develop a model to forecast civilian personnel inventory for the National Security Agency (NSA). Accurate prediction of personnel inventories will help the NSA with issues ranging from hiring, promotion, and ethnic/gender diversity to the development of cost-effective force reduction programs. The model must be capable of producing multiple-year forecasts of the NSA's civilian force structure with a minimum fidelity level that allows for break-out by years-of service, career field, and grade. Historical data will be utilized to estimate logistic regression parameters that will compose the internal workings of the model. The JMP statistical software package will be used for data analysis, while the model will be developed as a Microsoft Excel application.
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