Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

1.4K
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...
1.4K
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

4.3K
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...
4.3K
Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

5.0K
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...
5.0K
Derivatives of Inverse Trigonometric Functions01:30

Derivatives of Inverse Trigonometric Functions

566
A ship tracking an approaching aircraft relies on geometric measurements to find out the aircraft’s position relative to the observer. By measuring the slant distance to the aircraft and the angle of elevation, the horizontal and vertical components of the distance can be obtained using trigonometric relationships. This geometric approach provides a basis for analyzing how the observed angle changes as the aircraft moves closer to the ship.To examine the mathematical behavior of the angle...
566
Glassware Calibration01:11

Glassware Calibration

2.0K
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...
2.0K
Inverse Trigonometric Functions01:29

Inverse Trigonometric Functions

543
Inverse trigonometric functions are fundamental mathematical tools that reverse the actions of standard trigonometric functions. While trigonometric functions map angles to ratios, inverse trigonometric functions perform the opposite operation by mapping a ratio back to its corresponding angle. These functions are essential in various applications, particularly in determining angles when given specific distances, such as calculating elevation angles in navigation and engineering.For a function...
543

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Influence of aged and non-aged environmentally relevant microplastics on zinc removal from aqueous media by Daphnia magna.

Analytical and bioanalytical chemistry·2026
Same author

Improving the SSIR Method: Implementation of an Exhaustive Multilevel Scan for Categorical Variables.

International journal of molecular sciences·2026
Same author

Photoredox catalysis leading to triazolo-quinoxalinones at room temperature: selectivity of the rate determining step.

Organic & biomolecular chemistry·2022
Same author

A predictive journey towards <i>trans</i>-thioamides/amides.

Chemical communications (Cambridge, England)·2022
Same author

Free-Radical Photopolymerization for Curing Products for Refinish Coatings Market.

Polymers·2022
Same author

Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method.

Biomolecules·2020
Same journal

Aptamer-CRISPR Glucose Transducer for point-of-care IgE detection.

Talanta·2026
Same journal

Dual-channel fluorescent probes enable synchronous tracking of peroxynitrite and cysteine in mitochondrial redox dynamics.

Talanta·2026
Same journal

A versatile graphene-like film as a chemo-resistive platform for selective ammonia gas sensing.

Talanta·2026
Same journal

Enhanced determination of 85 mycotoxins in challenging root and rhizome herbal medicines using online segmented multi-dimensional liquid chromatography-tandem mass spectrometry.

Talanta·2026
Same journal

Tailoring oxygen vacancy of WO<sub>3</sub> nanoparticles for high-performance gas sensing: room-temperature NO<sub>2</sub> and low-temperature triethylamine detection.

Talanta·2026
Same journal

Mixed potential acetone sensor based on LaBaCo<sub>2-x</sub>Fe<sub>x</sub>O<sub>5±δ</sub> (x=0, 0.05 and 0.2) sensing electrode and yttria-stabilized zirconia for non-invasive diagnosis of diabetes.

Talanta·2026
See all related articles

Related Experiment Video

Updated: May 6, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

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

Published on: September 7, 2019

10.8K

The connection between inverse and classical calibration.

Emili Besalú1

  • 1Department of Chemistry and Institute of Computational Chemistry and Catalysis, Universitat de Girona, Av. Montilivi s/n, 17071 Girona, Spain.

Talanta
|October 24, 2013
PubMed
Summary
This summary is machine-generated.

This study reveals a counterintuitive method for improving calibration accuracy. By correcting observed values before inputting them into classical calibration, users achieve results equivalent to inverse calibration, enhancing prediction accuracy for independent variables.

Keywords:
Classical calibrationInverse calibrationLinear equationRegression towards the mean

More Related Videos

Calibration Procedures for Orthogonal Superposition Rheology
08:43

Calibration Procedures for Orthogonal Superposition Rheology

Published on: November 18, 2020

2.0K
Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration
07:03

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Published on: February 23, 2017

7.4K

Related Experiment Videos

Last Updated: May 6, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

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

Published on: September 7, 2019

10.8K
Calibration Procedures for Orthogonal Superposition Rheology
08:43

Calibration Procedures for Orthogonal Superposition Rheology

Published on: November 18, 2020

2.0K
Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration
07:03

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Published on: February 23, 2017

7.4K

Area of Science:

  • Analytical Chemistry
  • Metrology

Background:

  • Classical calibration (regression of y on x) assumes observed dependent variables (yobs) directly represent the true values.
  • This assumption can lead to systematic deviations in the calculated independent variable (x) values.

Purpose of the Study:

  • To demonstrate a method for reducing systematic deviations in independent variable (x) predictions.
  • To explain the equivalence between a corrected classical calibration approach and inverse calibration (regression of x on y).

Main Methods:

  • Distinguishing between observed (yobs) and calculated (ycalc) dependent variables.
  • Applying a regression towards the mean effect correction to observed dependent variables.
  • Comparing the corrected classical calibration approach with direct inverse calibration.

Main Results:

  • Transforming observed y values via regression towards the mean before classical calibration yields improved x predictions.
  • This corrected classical calibration is mathematically equivalent to performing inverse calibration in a single step.
  • The inverse calibration approach generally offers superior numerical performance for interpolated x value predictions.

Conclusions:

  • Correcting observed data for regression towards the mean is crucial for accurate classical calibration.
  • Inverse calibration provides a more robust method for predicting independent variables, especially with interpolated data.
  • Understanding the relationship between yobs, ycalc, and regression effects enhances calibration model reliability.