Short answer: measurement uncertainty evaluated by statistical analysis of measurement or test results. According to the Vocabulary in Metrology, Type A evaluation of measurement uncertainty is an “evaluation of a component of measurement uncertainty by a statistical analysis of measured quantity values obtained under defined measurement conditions.” Example Examples of a Type A uncertainty […]
Short answer: The most significant sources of uncertainty vary with each type of test, measurement, and measurement system. However, some of the most common sources of uncertainty that significantly affect measurement results include: Repeatability, Reproducibility, Resolution, Drift or Stability, Bias, Reference Standard Uncertainty, Environmental Contributors, and Method-specific Contributors. Every test and measurement is different. […]
Collecting Data Before you can analyze and evaluate the measurement system and process, you must collect some data. However, before diving in head first, there are some things that should be considered. Review the Plan First, review your plan. If you do not, you may find yourself repeating the experiment. It is more time efficient […]
Collecting Data The number of samples collected during experimentation has an effect on the analysis of results and the validity of the test data collected. Over the years, I have observed several conflicting accounts of how many samples one should collect during experimentation. According to many introductory statistics textbooks, the number of samples collected depends […]
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