Measurement Uncertainty Applied to Cost-Effective Testing
The report shows how the methodology of measurement uncertainty can usefully be applied to test programs in order to optimize resources and save money. In doing so, it stresses the importance of integrating the generation of the Defined Measurement Process into more conventional project management techniques to create a Test Plan that allows accurate estimation of resources and trouble-free execution of the actual test. Finally, the report describes the need for post-test review and the importance of recycling lessons learned for the next project.
Rationale: This revision will streamline and clarify existing content and add examples using measurement uncertainty to estimate the Power and Confidence level of the experiment which are indicators of the probability that the experiment produced the correct result.