Measurement Precision
Measurement Precision - Related Videos
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...
07:04
High Precision Zinc Isotopic Measurements Applied to Mouse Organs
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Cited by 28 •
2015
We present the technique to measure with high precision zinc isotope ratios in mouse organs.
09:36
Measurement of Spatial Stability in Precision Grip
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Cited by 2 •
2020
The goal of this protocol is to measure the center of pressure (COP) replacement using a high spatial resolution sensor sheet to reflect the spatial stability in a precision grip. The use of this protocol could contribute to greater understanding of the physiology and pathophysiology of grasping.
07:57
Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
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Cited by 65 •
2014
Accuracy is a major demand in dental medicine. To verify accuracy, reference scanners are needed. This article presents a new reference scanner with an adjusted scanning method to acquire a broad variety of dental morphologies with high trueness and precision.
00:10
Precision Measurements and Parametric Models of Vertebral Endplates
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Cited by 1 •
2019
A reverse engineering system is employed to record and obtain detailed and comprehensive geometry data of vertebral endplates. Parametric models of vertebral endplate are then developed, which are beneficial to designing personalized spinal implants, making clinical diagnoses, and developing accurate finite element models.
FAQs
Precision describes the consistency among repeated results, whereas accuracy concerns how close a result is to the true or accepted value. A method can therefore produce tightly grouped measurements while still giving an inaccurate result. Chemists evaluate both properties separately so that reproducible data are not mistaken for correct data.
Instrument resolution, sample handling, and consistency in carrying out the procedure all affect the spread of repeated results. Random error also contributes to variation between measurements. Controlling these factors helps reduce unwanted differences and makes it easier to determine whether observed variability comes from the method, the equipment, or the handling of the sample.
These measures describe how widely repeated measurements differ from one another. The range compares the most separated results, while variance and standard deviation summarize variation across the data set. Smaller values indicate tighter agreement among measurements, allowing chemists to compare the consistency of analyses and identify procedures that produce greater variability.
Chemists perform repeated analyses under the same conditions, keeping the sample treatment, instrument use, and procedural steps as consistent as possible. They then examine the resulting spread with a range, variance, or standard deviation. This workflow reveals the method's repeatability and helps identify variability that may require procedural or equipment-related investigation.
When two analytical methods are applied repeatedly under comparable conditions, their variation can be evaluated using the same statistical measure. The method producing the smaller spread demonstrates greater precision for that comparison. Such evaluations support method selection and validation, particularly when consistent quantitative results are important for chemical analysis.
Precision helps chemists decide how many significant figures a result can reasonably support. Reporting more digits than the observed variation justifies can imply unwarranted reliability. Precision assessment also strengthens quality control by revealing inconsistent analyses, supporting reproducible research, and showing whether an experimental procedure performs consistently over repeated measurements.