Measurement Uncertainty
Measurement Uncertainty - Related Videos
02:46
Uncertainty in Measurement: Reading Instruments
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2020
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
03:34
Uncertainty in Measurement: Significant Figures
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2020
All the digits in a measurement, including the uncertain last digit, are called significant figures or significant digits. Note that zero may be a measured value; for example, if a scale that shows weight to the nearest pound reads “140,” then the 1 (hundreds), 4 (tens), and 0 (ones) are all significant (measured) values. A measurement result is properly reported when its significant digits accurately represent the certainty of the measurement process. Below are a set of rules to determine the...
03:37
Uncertainty in Measurement: Accuracy and Precision
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2020
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Suppose a quality control...
04:08
The Uncertainty Principle
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2020
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He mathematically...
09:07
Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
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Cited by 4 •
2015
To date research has focused on cognitive strategies people adopt to cope with uncertainty. This research examines instead an experiential way of dealing with uncertainty and introduces a set of experimental methods showing how the experience of haptic softness can serve as a tool to deal with uncertainty.
FAQs
Random effects produce variation among repeated results, so their contribution can be estimated by measuring the same quantity more than once. Systematic effects instead arise from consistent influences, such as calibration or procedural limitations, and may shift results in one direction. Increasing the number of measurements helps characterize random variation but does not automatically eliminate a systematic contribution.
Each factor can limit how closely a reported result represents the quantity being measured. Instrument resolution restricts the detail that can be displayed, calibration can introduce a consistent measurement effect, sampling may fail to represent the material adequately, and procedural limitations can affect execution. Considering these sources prevents uncertainty estimates from relying only on repeated readings.
Uncertainty propagation combines the uncertainty contributions from measurements used in a calculation. A result based on multiple inputs therefore requires attention to the reliability of each input, not just the final numerical operation. This approach shows how limitations in separate measurements influence the calculated chemical value and supports reporting a result with an appropriate overall uncertainty.
Begin by identifying relevant sources, including random variation, instrument resolution, calibration, sampling, and procedural limitations. Use repeated measurements to characterize variation where appropriate, assess the other contributions, and combine the effects when calculations use multiple measurements. The final reported value should then include an uncertainty that reflects the complete measurement process rather than a single instrument reading.
Significant figures should communicate the precision supported by the measurement and its uncertainty, rather than suggesting that every displayed digit is exact. Reporting an uncertainty alongside the result makes the implied precision visible and helps readers judge the reliability of the value. This practice is especially important when calculated results might otherwise appear more precise than the measurements used.
A chemical result becomes more useful for evaluation when its uncertainty accompanies the numerical value. The result can then be compared meaningfully with a reference value or an acceptance criterion, while the uncertainty indicates how confidently that comparison should be interpreted. In method validation and instrument assessment, this supports judgments about analytical performance instead of relying on numerical agreement alone.