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The Department of Defense (DoD) testing methodology for the evaluation and acceptance between existing and emerging automatic measurement systems are based on qualitative (PASS/FAIL) criteria of the automatic measurement systems responses when testing of a unit-under-test. Acceptance of a unit-under-test, based on qualitative responses, is contingent upon accurate measurements by the automatic measurement system. This dissertation presents a regression analysis methodology for evaluating the performance between automatic measurement systems that are functionally equivalent but technologically different. The motivation for this research is to advance regression analysis techniques in the transportability of unit-under-tests between current and emerging measurement systems. Given the acquisition cost, schedule and technical challenges in developing new systems, this methodology will provide increased confidence for the acquisition community to make informed decisions about the capability of future automatic measurement systems. The regression analysis methodology presented, quantitatively analyzes the parametric responses by functionally decomposing the automatic measurement systems to their lowest functional capability, and subsequently integrates the total automated measurement system for a unit-under-test's parametric responses. The result from this research provides an in-depth analysis of the measurement variance and contributors to the overall performance between the automatic measurement systems.

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