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Related Concept Videos

Uncertainty in Measurement: Reading Instruments02:46

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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...
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In any measurement, the precision of the measuring tool is an essential factor. An ordinary ruler, for example, can measure length to the closest millimeter; a caliper, on the other hand, can measure length to the nearest 0.01 mm. As a result, the caliper is a more precise measurement tool because it can measure extremely minute changes in length. The measurements will be more accurate if the measuring tool is more precise.
It should be emphasized that when we represent measured values, the...
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Measurement: Standard Units03:38

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Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.
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Measurement: Derived Units03:02

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The International System of Units or SI system, by international agreement, has fixed measurement units for seven fundamental properties: length, mass, time, temperature, electric current, amount of substance, and luminosity. These are called the SI base units.
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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. 
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SI Units: 2019 Redefinition01:13

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Measurement is an indispensable part of analytical chemistry. The result of measurement helps quantify a substance's physical property and compare it with the physical property of another substance. Each measurement comprises two components - a number indicating the magnitude and a unit of measurement as a standard for comparison. Further, the same quantity can be measured using different units of measurement, which leads to differences in magnitude.
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Related Experiment Video

Updated: May 1, 2026

Applicability Analysis of Assessment Methods for Morphological Parameters of Corroded Steel Bars
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Applicability Analysis of Assessment Methods for Morphological Parameters of Corroded Steel Bars

Published on: November 1, 2018

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The measurement method matters.

Holger Klein1

  • 1Université Grenoble Alpes and Centre National de la Recherche Scientifique, 25 rue des Martyrs - BP 166, 38042 Grenoble, France.

Iucrj
|April 30, 2026
PubMed
Summary
This summary is machine-generated.

This study discusses the systematic comparison of 3D electron diffraction (3D-ED) methods, focusing on their data quality. It provides insights into the performance and reliability of different 3D-ED techniques for crystallographic analysis.

Keywords:
3D EDbenchmarkingelectron diffractionstructure determination

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Area of Science:

  • Crystallography
  • Materials Science
  • Data Analysis

Background:

  • 3D electron diffraction (3D-ED) is a powerful technique for crystal structure determination.
  • Evaluating the data quality of different 3D-ED methods is crucial for reliable structural analysis.
  • Previous comparisons have often focused on specific aspects, necessitating a systematic overview.

Purpose of the Study:

  • To systematically compare various 3D-ED methods.
  • To evaluate and contrast the data quality obtained from different 3D-ED approaches.
  • To provide a benchmark for selecting appropriate 3D-ED techniques based on data quality.

Main Methods:

  • Literature review and synthesis of existing studies on 3D-ED.
  • Analysis of data quality metrics reported for different 3D-ED methodologies.
  • Discussion of factors influencing data quality in 3D-ED experiments.

Main Results:

  • Schmitt et al. presented a systematic comparison of 3D-ED methods.
  • The comparison focused on critical aspects of data quality.
  • Specific findings regarding the relative performance of methods are detailed in the referenced work.

Conclusions:

  • A comprehensive understanding of 3D-ED data quality is essential.
  • The systematic comparison aids researchers in choosing optimal 3D-ED methods.
  • Further advancements in 3D-ED techniques should prioritize data quality improvements.