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Acquisition Program Problem Detection Using Text Mining Methods, Trevor P. Miller
Acquisition Program Problem Detection Using Text Mining Methods, Trevor P. Miller
Theses and Dissertations
This research provides program analysts and Department of Defense leadership with an approach to identify problems in real-time for acquisition contracts. Specifically, we test the abilities of statistical algorithms using text mining techniques to detect unusual changes in acquisition programs’ cost estimates at the completion of the programs. Currently, the government purchases monthly written reports, an informational tool on status of an acquisition program, but has not been integrated into problem prediction analysis. We center our research on the following two questions: First, can we quantify the qualitative written reports? Second, can we use these quantifications of the texts to …
Logistic And Multiple Regression: The Two-Step Approach To Estimating Cost Growth, Daniel C. Genest
Logistic And Multiple Regression: The Two-Step Approach To Estimating Cost Growth, Daniel C. Genest
Theses and Dissertations
This study sought to predict cost growth in major Department of Defense (DoD) acquisition programs using logistic and multiple regression. In recent years, the use of statistical regression has proven to be successful in predicting the relationships associated with cost growth. This research follows on the work of Sipple (2002) and Bielecki (2003) and further explores the possibilities of using statistical regression to accurately estimate the dollar value associated with risk and uncertainty early in a program's life cycle. In doing so, the author intends to reduce cost growth by increasing the accuracy of the original cost estimates subsequently used …