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The level of measurement – known as the scale, index, or typology – will determine what can be concluded from the data. A yes/no question will only reveal how many of the sample group answered yes or no, lacking the resolution to determine an average response. The nature of the expected responses should be defined and retained for ...
In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions. [7] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value.
If the mass of an object is estimated as 3.78 ± 0.07 kg, so the actual mass is probably somewhere in the range 3.71 to 3.85 kg, and it is desired to report it with a single number, then 3.8 kg is the best number to report since its implied uncertainty ± 0.05 kg gives a mass range of 3.75 to 3.85 kg, which is close to the measurement range.
measurement resolution, be it spatial, temporal, or otherwise; curve fitting, typically for linearity, which justifies interpolation between calibrated reference points; robustness, or the insensitivity to potentially subtle variables in the test environment or setup which may be difficult to control
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A measurement system analysis (MSA) is a thorough assessment of a measurement process, and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process. Just as processes that produce a product may vary, the process of obtaining measurements and data may also have variation ...
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or "reasonable". This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to "reasonable" conclusions that use: quantitative, statistical, and ...
where the partials are evaluated at the mean of the respective measurement variable. (For more than two input variables this equation is extended, including the various mixed partials.) Returning to the simple example case of z = x 2 the mean is estimated by