Читать книгу Planning and Executing Credible Experiments - Robert J. Moffat - Страница 19

An experiment is a system designed to make a measurement. The system consists of the hardware (test rig and specimens), the instruments (including sensors, amplifiers, extension wires, etc.), and the interpretive software (calibration routines, data reduction programs, etc.). The whole system is an instrument designed to make a particular kind of measurement. As such, the system must be designed so that it can be calibrated. The system must be calibrated before it is used to generate new data. It must be possible, using diagnostic tests on the system, to confirm the accuracy of the measurements made with the system.

This view of an experiment is illustrated in Figure 1.1, which also shows some of the necessary features of the system design.

Perhaps the most important feature of this view of experimental work is the important role given to uncertainty analysis. There are uncertainties in every measurement and, therefore, in every parameter calculated using experimental data. When the results of an experiment scatter (i.e. are different on repeated trials), the question always arises, “Is this scatter due to the uncertainties in the input data or is something changing in the experiment?”

Uncertainty analysis provides the proven credible way to answer that question. By quantifying and reporting the uncertainty of each value, we allow our client confidence and credence in our results. Figure 1.1 shows the uncertainty analysis as a key part of the data reduction program, although it is too often neglected. Using either Root‐Sum‐Squared estimation or Monte Carlo simulation, the uncertainty in experimental results can be calculated with little additional effort on the part of the experimenter.

Figure 1.1 The experiment viewed as an instrument. Adjust the instrument by analyzing Uncertainty in each Bubble.