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

Coefficient of Correlation01:12

Coefficient of Correlation

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the lowest drug...
Calculating and Interpreting the Linear Correlation Coefficient01:11

Calculating and Interpreting the Linear Correlation Coefficient

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
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...
Correlation of Experimental Data01:23

Correlation of Experimental Data

Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity, and...
Correlations02:20

Correlations

Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...

You might also read

Related Articles

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

Sort by
Same author

Corrigendum: Interpretation guidance for MHRA regulatory considerations for phage therapeutic products.

Microbiology (Reading, England)·2026
Same author

Interpretation guidance for MHRA regulatory considerations for phage therapeutic products.

Microbiology (Reading, England)·2025
Same author

Resensitizing the Untreatable: Zidovudine and Polymyxin Combinations to Combat Pan-Drug-Resistant <i>Klebsiella pneumoniae</i>.

Pharmaceuticals (Basel, Switzerland)·2025
Same author

Precise Determination of the Strong Coupling Constant from Dijet Cross Sections up to the Multi-TeV Range.

Physical review letters·2025
Same author

Feasibility of serial measurement of nitrite for pharmacodynamic monitoring and precision prescribing in urinary tract infections.

Communications medicine·2025
Same author

Acute Lymphoblastic Leukemia and Associated HLA-A, B, DRB1, and DQB1 Molecules: A Moroccan Pediatric Case-Control Study.

International journal of molecular sciences·2025
Same journal

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor.

Optics express·2026
Same journal

Robust 3D topography measurement of large-range high-aspect-ratio structures based on dual-domain statistical filtering in SD-OCT.

Optics express·2026
Same journal

Broadband transmissive terahertz metasurface for simultaneous quad-mode OAM multiplexing.

Optics express·2026
Same journal

Leveraging two-dimensional materials for high-sensitivity optical sensors: quasi-bound states in the continuum within hybrid metasurfaces.

Optics express·2026
Same journal

Resolution investigation for dual-spherical-wave optical scanning holographic microscopy: methods and performance.

Optics express·2026
Same journal

Robustness of parallel subnetwork-filtered diffractive deep neural networks.

Optics express·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 2026

New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies
05:59

New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies

Published on: October 6, 2023

Using coherence to measure two-time correlation functions.

Mark Sutton, Khalid Laaziri, F Livet

    Optics Express
    |May 28, 2009
    PubMed
    Summary
    This summary is machine-generated.

    X-ray intensity fluctuation spectroscopy measures two-time correlation functions. This technique analyzes equilibrium fluctuations in gold colloids and non-equilibrium unmixing in AlLi alloys.

    More Related Videos

    Measurement of X-ray Beam Coherence along Multiple Directions Using 2-D Checkerboard Phase Grating
    10:39

    Measurement of X-ray Beam Coherence along Multiple Directions Using 2-D Checkerboard Phase Grating

    Published on: October 11, 2016

    Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
    08:51

    Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

    Published on: November 1, 2019

    Related Experiment Videos

    Last Updated: Jun 22, 2026

    New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies
    05:59

    New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies

    Published on: October 6, 2023

    Measurement of X-ray Beam Coherence along Multiple Directions Using 2-D Checkerboard Phase Grating
    10:39

    Measurement of X-ray Beam Coherence along Multiple Directions Using 2-D Checkerboard Phase Grating

    Published on: October 11, 2016

    Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
    08:51

    Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

    Published on: November 1, 2019

    Area of Science:

    • Materials Science
    • Condensed Matter Physics
    • Spectroscopy

    Background:

    • Coherent X-ray sources produce speckle patterns.
    • Speckle patterns are sensitive to sample dynamics.
    • Understanding fluctuations is key to material properties.

    Purpose of the Study:

    • Introduce X-ray Intensity Fluctuation Spectroscopy (XIFS).
    • Demonstrate XIFS for measuring two-time correlation functions.
    • Apply XIFS to both equilibrium and non-equilibrium systems.

    Main Methods:

    • Utilized X-ray Intensity Fluctuation Spectroscopy.
    • Analyzed speckle patterns from coherent X-ray sources.
    • Measured two-time correlation functions of dynamic processes.

    Main Results:

    • Successfully measured equilibrium fluctuations in gold colloids within polystyrene.
    • Successfully measured non-equilibrium fluctuations during the unmixing of AlLi below the miscibility gap.
    • Demonstrated the capability of XIFS to probe diverse dynamic phenomena.

    Conclusions:

    • XIFS is a powerful technique for characterizing material dynamics.
    • The method is applicable to both equilibrium and non-equilibrium processes.
    • XIFS provides insights into colloidal and phase-separation dynamics.