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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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...
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

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...
Glassware Calibration01:11

Glassware Calibration

Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

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 other increases, and...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
The Scientific Method02:40

The Scientific Method

Research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

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Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
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Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

Calibration research: where do we go from here?

Linda Bol1, Douglas J Hacker

  • 1Department of Educational Foundations and Leadership, Old Dominion University Norfolk, VA, USA.

Frontiers in Psychology
|August 7, 2012
PubMed
Summary
This summary is machine-generated.

Calibration research explores the accuracy of self-performance judgments. This study identifies six key research directions to enhance understanding of calibration, including anchoring, incentives, and social influences on accuracy.

Keywords:
calibrationmetacognitionresearch methodsself-regulated learningsocial cognition

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Last Updated: May 19, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
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Published on: September 7, 2019

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08:16

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Area of Science:

  • Psychology
  • Educational Psychology
  • Cognitive Science

Background:

  • Calibration, the alignment between perceived and actual performance, is a significant area of research.
  • Existing literature reveals continued interest but also identifies gaps in understanding calibration processes.

Purpose of the Study:

  • To identify and propose six distinct research directions to advance calibration research.
  • To address current limitations and expand knowledge within the field of calibration.

Main Methods:

  • Literature review to identify research gaps.
  • Proposal of specific research questions and methodologies.
  • Identification of prior studies to guide future investigations.

Main Results:

  • Six key research directions are delineated: anchoring mechanisms, incentives/authenticity, self-reporting bases, group/social influences, absolute vs. relative accuracy, and predictive validity for achievement.
  • Proposed methods and relevant prior studies are suggested for each direction.

Conclusions:

  • Pursuing these six research directions can significantly enhance the understanding of calibration.
  • This framework provides a roadmap for future research to fill identified gaps in the literature.