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Experimental uncertainty analysis is a technique that analyses a derived quantity, based on the uncertainties in the experimentally measured quantities that are used in some form of mathematical relationship ("model") to calculate that derived quantity. The model used to convert the measurements into the derived quantity is usually based on fundamental principles of a science or engineering discipline.
The uncertainty has two components, namely, bias (related to accuracy) and the unavoidable random variation that occurs when making repeated measurements (related to precision). The measured quantities may have biases, and they certainly have random variation, so what needs to be addressed is how these are "propagated" into the uncertainty of the derived quantity. Uncertainty analysis is often called the "propagation of error."
and 28 Related for: Experimental uncertainty analysis information
Experimentaluncertaintyanalysis is a technique that analyses a derived quantity, based on the uncertainties in the experimentally measured quantities...
based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement limitations (e.g., instrument precision)...
different sources of uncertainty in its inputs. A related practice is uncertaintyanalysis, which has a greater focus on uncertainty quantification and...
epistemic uncertainties. Accuracy and precision Confidence interval Experimentaluncertaintyanalysis History of measurement Propagation of uncertainty Repeatability...
In physical experiments uncertaintyanalysis, or experimentaluncertainty assessment, deals with assessing the uncertainty in a measurement. An experiment...
enter mathematical models and experimental measurements in various contexts. One way to categorize the sources of uncertainty is to consider: Parameter This...
The uncertainty principle, also known as Heisenberg's indeterminacy principle, is a fundamental concept in quantum mechanics. It states that there is...
an n-norm. Accepted and experimental value Condition number Errors and residuals in statistics Experimentaluncertaintyanalysis Machine epsilon Measurement...
learning Accepted and experimental value Data quality Engineering tolerance Exactness (disambiguation) Experimentaluncertaintyanalysis F-score Floating point...
design of experiments (DOE or DOX), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the...
The analysis of variance provides the formal tools to justify these intuitive judgments. A common use of the method is the analysis of experimental data...
terms, risk is the possibility of something bad happening. Risk involves uncertainty about the effects/implications of an activity with respect to something...
Uncertainty or incertitude refers to epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical...
chemistry List of chemical analysis methods List of materials analysis methods Measurement uncertainty Metrology Sensory analysis - in the field of Food science...
pp. 195–220. Raiffa, Howard (1997). Decision Analysis: Introductory Lectures on Choices Under Uncertainty. McGraw Hill. ISBN 978-0-07-052579-5. Ramsey...
observational study does not involve experimental manipulation. Two main statistical methods are used in data analysis: descriptive statistics, which summarize...
and Head Experimental Brewer of Guinness and was a pioneer of modern statistics. He pioneered small sample experimental design and analysis with an economic...
unlimited in the other). This is an elementary form of an uncertainty principle in a harmonic-analysis setting. Fourier series can be conveniently studied in...
C6+ fraction. For "pipeline quality" natural gas, a C9+ GC analysis may reduce the uncertainty, because it eliminates the C6-C8 distribution error. However...
finished product of the analysis). The general type of entity upon which the data will be collected is referred to as an experimental unit (e.g., a person...
distribution. They can also be used to model phenomena with significant uncertainty in inputs, such as calculating the risk of a nuclear power plant failure...
In the design of experiments, optimal experimental designs (or optimum designs) are a class of experimental designs that are optimal with respect to some...
of addressing the scientific or technological obstacle/uncertainty by experimentation or analysis must be clearly set out. Scientific or technological advancement:...
the significant uncertainty in the measured value of G in terms of other known fundamental constants, a similar level of uncertainty will show up in the...
typically performed using experimental apparatus such as wind tunnels. In addition, previously performed analytical or empirical analysis of a particular problem...
The uncertainty reduction theory, also known as initial interaction theory, developed in 1975 by Charles Berger and Richard Calabrese, is a communication...
attempt to calibrate non-statistical uncertainty (flaws in underlying assumptions). When combined with meta-analysis this method can be used to understand...
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