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A Production Early Warning System (PEWS) Model Which Predicts Future USAREC Mission Accomplishment
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
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This thesis develops a framework for a statistical Production Early Warning System PEWS model which predicts the United States Army Recruiting Commands contract production. Model predictions are based on the initial Armed Forces Qualification Test AFQT taken by applicants over the past two years, the number of applicants expected to take the AFQT throughout the projection period, the historical probability that an applicant will sign a contract, and the distribution of time from when applicants take the AFQT until they sign a contract. Model parameters are based on the last five years of historical testing and contracting data. Yearly, seasonal, and monthly trends are incorporated by analyzing historical data using semi-monthly segments split on the 15th of the month. The model predicts contract production overall and for seven separate mission box categories. Performance of the model is measured by subtracting the number of actual contracts from the number of predicted contracts, and dividing by the number of actual contracts for FY 1993 time periods. The models accuracy is greatly reduced because the testing data base does not include applicants who took the AFQT as part of a batch test group.
APPROVED FOR PUBLIC RELEASE