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For example, an experimental uncertainty analysis of an undergraduate physics lab experiment in which a pendulum can estimate the value of the local gravitational acceleration constant g. The relevant equation [1] for an idealized simple pendulum is, approximately,
Measurement errors can be divided into two components: random and systematic. [2] Random errors are errors in measurement that lead to measurable values being inconsistent when repeated measurements of a constant attribute or quantity are taken. Random errors create measurement uncertainty. Systematic errors are errors that are not determined ...
Fornasini, Paolo (2008), The uncertainty in physical measurements: an introduction to data analysis in the physics laboratory, Springer, p. 161, ISBN 978-0-387-78649-0 Meyer, Stuart L. (1975), Data Analysis for Scientists and Engineers , Wiley, ISBN 978-0-471-59995-1
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.
Measurements are usually subject to variation and measurement uncertainty; thus they are repeated and full experiments are replicated to help identify the sources of variation, to better estimate the true effects of treatments, to further strengthen the experiment's reliability and validity, and to add to the existing knowledge of the topic. [19]
Since the announcement of Pons and Fleischmann in 1989, cold fusion has been considered to be an example of a pathological science. [15] Two panels convened by the US Department of Energy, one in 1989 and a second in 2004, did not recommend a dedicated federal program for cold fusion research. [16]
In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale.. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation.
In this case, even if there is no unknown parameter in the model, a discrepancy is still expected between the model and true physics. Algorithmic Also known as numerical uncertainty, or discrete uncertainty. This type comes from numerical errors and numerical approximations per implementation of the computer model.