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

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

24.1K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
24.1K
Scatter Plot01:15

Scatter Plot

8.5K
The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
8.5K
Interval Level of Measurement00:55

Interval Level of Measurement

13.0K
For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
13.0K
Ratio Level of Measurement00:54

Ratio Level of Measurement

13.6K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
13.6K
Orders of Magnitude01:15

Orders of Magnitude

19.7K
The order of magnitude of a number is the power of 10 that most closely approximates it. Thus, the order of magnitude estimates the scale (or size) of its value. To find the order of magnitude of a number, take the base-10 logarithm of the number and round it to the nearest integer. Then the order of magnitude of the number is simply the resulting power of 10.
The order of magnitude is simply a way of rounding numbers consistently to the nearest power of 10. This makes doing rough mental math...
19.7K
The Dot Product01:26

The Dot Product

332
Measuring how one directional quantity affects another along a specific path involves comparing their orientation and strength. When two such quantities are represented using direction and amount, a numerical result is computed to show how much one acts along the path of the other. This result comes from a rule combining both inputs' horizontal and vertical parts and adding the results.This calculation gives a single value that grows larger when both inputs point in similar directions and...
332

You might also read

Related Articles

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

Sort by
Same author

3D epithelial cell topology tunes signaling range to promote precise patterning.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Molecular structure of the ESCRT-III-based archaeal CdvAB cell division machinery.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

The mechanism of cell-cycle-dependent proteasomal degradation of archaeal ESCRT-III homolog CdvB in Sulfolobus.

The EMBO journal·2026
Same author

Bridging single cells to organs: Mesoscale modules as fundamental units of tissue function.

Cell·2025
Same author

Temporal and spatial coordination of DNA segregation and cell division in an archaeon.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

High-throughput mechanomic screening reveals novel regulators of single-cell mechanics.

Biophysical journal·2025

Related Experiment Video

Updated: Apr 26, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

4.7K

An absolute interval scale of order for point patterns.

Emmanouil D Protonotarios1, Buzz Baum2, Alan Johnston3

  • 1CoMPLEX, University College London, London, UK Department of Computer Science, University College London, London, UK emmanouil.protonotarios.10@ucl.ac.uk.

Journal of the Royal Society, Interface
|August 1, 2014
PubMed
Summary

Human observers consistently judge the order in point patterns. A new geometric algorithm quantifies this order on an interval scale, proving more accurate than existing measures.

Keywords:
orderpoint patternpsychophysical scaling

More Related Videos

Pattern Generation for Micropattern Traction Microscopy
09:26

Pattern Generation for Micropattern Traction Microscopy

Published on: February 17, 2022

2.1K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.1K

Related Experiment Videos

Last Updated: Apr 26, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

4.7K
Pattern Generation for Micropattern Traction Microscopy
09:26

Pattern Generation for Micropattern Traction Microscopy

Published on: February 17, 2022

2.1K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.1K

Area of Science:

  • * Perceptual science
  • * Computational geometry
  • * Biological pattern formation

Background:

  • * Human observers can reliably assess the degree of order in point patterns.
  • * Previous methods for quantifying pattern order lacked precision and a standardized scale.

Purpose of the Study:

  • * To establish a consistent, interval scale for quantifying the order of point patterns.
  • * To develop a novel geometric algorithm for precise order measurement.
  • * To validate the algorithm's utility in a biological context.

Main Methods:

  • * Pairwise ranking of 20 point patterns by human observers to establish a perceptual order scale.
  • * Development of a geometric algorithm analyzing inter-point spacing variability.
  • * Anchoring the algorithm's output to known points (Poisson processes, perfect lattices) to create an absolute scale.

Main Results:

  • * Human judgments of point pattern order are highly consistent across individuals.
  • * The new geometric algorithm achieves 70% greater accuracy than existing measures.
  • * An absolute interval scale of order was constructed, calibrated in just-notable-differences (jnds).

Conclusions:

  • * A robust, geometrically derived interval scale accurately quantifies visual order in point patterns.
  • * The developed algorithm provides a precise and reliable method for order assessment.
  • * The scale's biological application demonstrates its effectiveness in analyzing developmental patterns, such as fruit fly bristle formation.