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

Ranks01:02

Ranks

572
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
572
Components of Stress01:23

Components of Stress

633
Stress analysis under multiple loading conditions is intricate, necessitating a comprehensive grasp of normal and shearing stresses. Consider a small cube at point O, subjected to stress on all six faces, visible or not. Normal stress components σx, σy, σz act perpendicularly to the x, y, and z axes. Shearing stress components τxy and τxz are exerted on faces perpendicular to these axes.
Interestingly, the hidden cube faces also experience these stresses, equal and...
633
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

561
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
561
General State of Stress01:21

General State of Stress

781
The general state of stress within a material can be accurately depicted using a stress tensor. This tensor encapsulates the internal forces distributed within a material subjected to external forces or deformations.
Specifically, consider a tetrahedral element where one face, labeled XYZ, is perpendicular to the line OA, and the remaining faces align with the coordinate axes with point O as the origin. At any point, such as point O, the stress tensor can be used to determine the stress...
781
Principal Stresses01:24

Principal Stresses

1.0K
The graphical depiction of normal and shearing stress equations is represented by a circle, demonstrating the interplay between these stresses under different angular conditions. The center of this circle C, located on the vertical axis, represents the average normal stress, while its radius shows the range of stress variations. At points A and B, where the circle intersects the horizontal axis, the maximum and minimum normal stresses are observed, occurring without shearing stress. These...
1.0K
Principal Stresses: Problem Solving01:15

Principal Stresses: Problem Solving

672
When analyzing two planes intersecting at right angles under the influence of shearing, tensile, and compressive stresses, it is essential to identify principal planes, maximum shearing stress, and principal stresses. To find the principal planes, apply a formula that equates them to twice the shearing stress divided by the difference between tensile and compressive stresses.
672

You might also read

Related Articles

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

Sort by
Same author

A Simple Approximation For Random Rankings Stress Values.

Multivariate behavioral research·2016
Same author

THE DETERMINATION OF THE UNDERLYING DIMENSIONALITY OF AN EMPIRICALLY OBTAINED MATRIX OF PROXIMITIES.

Multivariate behavioral research·2016
Same author

Effect of chronic exposure to lead on GABA binding in developing rat brain.

Neurochemistry international·2010
Same author

Long-term potentiation saturation in chronic cerebral hypoperfusion.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia·2008
Same author

Role of inhibition in chronic cerebral hypoperfusion.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia·2008
Same author

Chronic high dose captopril decreases total heart rate variability and increases heart rate in C57BL/6J mice.

International journal of cardiology·2008
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026
Same journal

betaselectr: Selective (and Proper) Standardization in Structural Equation Models.

Multivariate behavioral research·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

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

3.0K

A TABLE OF EXPECTED STRESS VALUES FOR RANDOM RANKINGS IN NONMETRIC MULTIDIMENSIONAL SCALING.

I Spence, J C Ogilvie

    Multivariate Behavioral Research
    |January 23, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a regression-based table to help determine if data is random. It aids users in analyzing empirical data sets with 12 to 48 objects across one to five dimensions.

    More Related Videos

    Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
    12:51

    Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

    Published on: June 16, 2018

    8.0K
    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
    06:02

    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

    Published on: October 6, 2020

    2.7K

    Related Experiment Videos

    Last Updated: Mar 26, 2026

    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

    3.0K
    Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
    12:51

    Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

    Published on: June 16, 2018

    8.0K
    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
    06:02

    Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

    Published on: October 6, 2020

    2.7K

    Area of Science:

    • Data analysis
    • Statistical modeling
    • Computational statistics

    Background:

    • Nonmetric multidimensional scaling (NMDS) is a technique used to visualize similarities in high-dimensional data.
    • Distinguishing random data from structured patterns is crucial in various scientific fields.
    • Existing methods for assessing data randomness can be complex or limited in scope.

    Purpose of the Study:

    • To develop a practical tool for assessing the randomness of empirical data sets.
    • To provide a user-friendly method for interpreting the results of nonmetric multidimensional scaling.
    • To establish a quantitative basis for deciding if observed data patterns are likely random.

    Main Methods:

    • Application of a nonmetric multidimensional scaling (NMDS) algorithm to pseudo-random data sets.
    • Utilizing regression techniques to model the relationship between NMDS outputs and data characteristics.
    • Construction of a decision-support table based on the regression models.

    Main Results:

    • A table was successfully constructed to aid in the assessment of data randomness.
    • The table covers data sets ranging from 12 to 48 objects (points).
    • The table accounts for recovered dimensions from one to five.

    Conclusions:

    • The developed table provides a valuable resource for researchers to evaluate the randomness of their data.
    • The regression-based approach offers a statistically sound method for data interpretation.
    • This tool can enhance the rigor of scientific conclusions drawn from empirical data analysis.