Date of Award

3-2006

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Mathematics and Statistics

First Advisor

Edward D. White, III, PhD

Abstract

Many databases rely on documents (research) of the past to input data to create a comprehensive database. The Selected Acquisition Report (SAR) is one such document. The SARs are pervasive documents that have undergone decades of scrutiny by Congress and watchdog organizations such as the Government Accountability Office. Since the SAR has undergone such massive evolutionary changes, creating an accurate acquisition database presents a daunting task for the analyst and researcher alike. This research concerns itself with one such database. From this prior research database, we look to fill in missing data. We first conduct a literature review to determine why we have database discontinuity. Indeed, a large part of our review entails SARs. We find there are no other complete sources for acquisition reporting. Also, the reason for missing data stems from 30 years of change within the Department of Defense administration. In addition, we grow concerned about the number of rebaselines a program undergoes in its lifecycle. Investigating this, we add the variable # of Rebaselines to schedule and cost regression models from prior research for statistical evaluation. We find our new variable is highly predictive with past schedule modeling but not predictive with prior cost modeling.

AFIT Designator

AFIT-GIR-ENC-06M-01

DTIC Accession Number

ADA445179

Download

Share

COinS