Quantifying Experimental Error
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Types Of Experimental Error
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Experimental Error Formula
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just how much the measured value is likely to deviate from the unknown, true, value of the quantity. The art of estimating these deviations should probably be called uncertainty analysis, but for historical reasons is referred to as experimental error calculation error analysis. This document contains brief discussions about how errors are reported, the kinds of measurement and error analysis lab report errors that can occur, how to estimate random errors, and how to carry error estimates into calculated results. We are not, and will not sources of error in physics be, concerned with the “percent error” exercises common in high school, where the student is content with calculating the deviation from some allegedly authoritative number. Significant figures Whenever you make a measurement, the number of meaningful digits that you write https://reference.wolfram.com/applications/eda/ExperimentalErrorsAndErrorAnalysis.html down implies the error in the measurement. For example if you say that the length of an object is 0.428 m, you imply an uncertainty of about 0.001 m. To record this measurement as either 0.4 or 0.42819667 would imply that you only know it to 0.1 m in the first case or to 0.00000001 m in the second. You should only report as many significant figures as are consistent with the estimated error. The quantity 0.428 m is said http://www.owlnet.rice.edu/~labgroup/pdf/Error_analysis.htm to have three significant figures, that is, three digits that make sense in terms of the measurement. Notice that this has nothing to do with the "number of decimal places". The same measurement in centimeters would be 42.8 cm and still be a three significant figure number. The accepted convention is that only one uncertain digit is to be reported for a measurement. In the example if the estimated error is 0.02 m you would report a result of 0.43 ± 0.02 m, not 0.428 ± 0.02 m. Students frequently are confused about when to count a zero as a significant figure. The rule is: If the zero has a non-zero digit anywhere to its left, then the zero is significant, otherwise it is not. For example 5.00 has 3 significant figures; the number 0.0005 has only one significant figure, and 1.0005 has 5 significant figures. A number like 300 is not well defined. Rather one should write 3 x 102, one significant figure, or 3.00 x 102, 3 significant figures. Absolute and relative errors The absolute error in a measured quantity is the uncertainty in the quantity and has the same units as the quantity itself. For example if you know a length is 0.428 m ± 0.002 m, the 0.002 m is an absolute error. The relative error (also called the fractional error) is obtained by dividing the absolute error in the quantity by
Health Search databasePMCAll DatabasesAssemblyBioProjectBioSampleBioSystemsBooksClinVarCloneConserved DomainsdbGaPdbVarESTGeneGenomeGEO DataSetsGEO ProfilesGSSGTRHomoloGeneMedGenMeSHNCBI Web SiteNLM CatalogNucleotideOMIMPMCPopSetProbeProteinProtein ClustersPubChem BioAssayPubChem CompoundPubChem SubstancePubMedPubMed HealthSNPSparcleSRAStructureTaxonomyToolKitToolKitAllToolKitBookToolKitBookghUniGeneSearch termSearch Advanced Journal list Help Journal ListBiophys https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2856138/ Jv.98(8); 2010 Apr 21PMC2856138 Biophys J. 2010 Apr 21; 98(8): 1566–1570. doi: 10.1016/j.bpj.2009.12.4297PMCID: PMC2856138Quantifying Subpixel Accuracy: An Experimental Method for Measuring Accuracy in Image-Correlation-Based, Single-Particle TrackingChristopher D. Saunter∗Department of Physics, Durham University, Durham, United KingdomChristopher D. Saunter: ku.ca.mahrud@retnuas.rehpotsirhc ∗Corresponding author ; Email: ku.ca.mahrud@retnuas.rehpotsirhcAuthor information ► Article notes ► Copyright and License information ►Received experimental error 2009 Aug 14; Accepted 2009 Dec 16.Copyright © 2010 by the Biophysical Society..This document may be redistributed and reused, subject to certain conditions.This article has been cited by other articles in PMC.AbstractSingle-particle tracking (SPT) is a range of powerful analysis techniques that measure particle motion from video microscopy image sequences. SPT is used to experimental error examples study the behavior of motor proteins and associated organelle transport within a cell. Many SPT algorithms deliver subpixel accurate measurements with noisy data corresponding to sub-10-nm resolution. Image-correlation techniques have been shown to be the most accurate method of tracking extended objects. However, to date, it has not been possible to determine the level of error when measuring the motion of an arbitrary particle with this method. In this article we derive a method for experimentally determining the accuracy of image-correlation-based SPT. We then apply this technique to a series of confocal fluorescence microscope image sequences of mitochondria, demonstrating the possibility of making measurements accurate to 5 nm when working with extended objects within live cells. In doing so we show that for particles with a low signal/noise ratio, the accuracy can vary by a factor of 2, corresponding to different particle shapes for a given signal/noise ratio. Use of the presented technique will allow researchers to quantify t
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