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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

807
Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
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Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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Accuracy and Precision01:52

Accuracy and Precision

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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.  Highly accurate...
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Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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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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Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

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In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
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Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

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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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Updated: Feb 17, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
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Calibration: Modelling the measurement process.

Eran Tal1

  • 1McGill University, Canada.

Studies in History and Philosophy of Science
|December 3, 2017
PubMed
Summary
This summary is machine-generated.

Calibration is a modeling activity that links measurement indications to outcomes. This model-based approach clarifies measurement accuracy and its connection to prediction, even without measurement standards.

Keywords:
CalibrationMeasurementMetrologyModelsPredictionUncertainty

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Area of Science:

  • Metrology
  • Philosophy of Science
  • Statistical Modeling

Background:

  • Calibration links measurement indications to outcomes.
  • Existing views on calibration lack a clear inferential structure.
  • The role of measurement standards is often overemphasized.

Purpose of the Study:

  • To analyze the inferential structure of calibration procedures.
  • To propose a model-based view of calibration.
  • To clarify the nature of measurement outcomes and accuracy.

Main Methods:

  • Analysis of the inferential structure of calibration.
  • Development of a theoretical and statistical model for measurement processes.
  • Examination of the relationship between measurement, prediction, and objectivity.

Main Results:

  • Calibration is fundamentally a modeling activity.
  • Measurement outcomes are parameter ranges that optimize model predictive accuracy and coherence.
  • Objectivity in measurement arises from well-defined models.
  • Measurement standards are not essential for calibration but aid in network coherence.

Conclusions:

  • A model-based perspective offers a robust framework for understanding calibration.
  • This view enhances clarity on measurement accuracy, objectivity, and the link to prediction.
  • Rethinking the necessity of measurement standards in calibration is proposed.