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

Introduction to the Sign Test01:10

Introduction to the Sign Test

1.4K
The sign test is an important tool in nonparametric statistics, offering a straightforward yet effective method for analyzing matched pairs, nominal data, or hypotheses concerning the median of a population. It transforms data points into positive or negative signs, avoiding the need for assumptions about data distribution and instead focusing on the direction of change. It is particularly valuable when data does not conform to the normal distribution requirements of many parametric tests. For...
1.4K
Sign Test for Median of Single Population01:20

Sign Test for Median of Single Population

391
In general, the sign test serves as a nonparametric method to test hypotheses about the median of a single population when the data does not follow a known distribution. This simplicity makes it particularly useful for small sample sizes or when the assumptions of parametric tests cannot be met. The process begins with identifying a null hypothesis, typically stating that the population median equals a specific value. The alternative hypothesis could be that the median is either not equal to,...
391
Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

444
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
444
Sign Test for Nominal Data01:12

Sign Test for Nominal Data

423
The sign test is a nonparametric method used to evaluate hypotheses about the median of a single sample or to compare the medians of two related samples. The sign test is particularly useful when dealing with nominal data, which includes distinct categories without an inherent order, such as names, labels, and preferences. Nominal data restricts statistical analysis to evaluating population proportions rather than mean or median values that require continuous data.
For example, consider a...
423
Statistical Significance01:50

Statistical Significance

22.9K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
22.9K
Significance Testing: Overview01:04

Significance Testing: Overview

12.9K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
12.9K

You might also read

Related Articles

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

Sort by
Same author

Design and Control of a 1-DOF MRI Compatible Pneumatically Actuated Robot with Long Transmission Lines.

IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division·2011
Same author

Effect of oxidized low-density lipoprotein concentration polarization on human smooth muscle cells' proliferation, cycle, apoptosis and oxidized low-density lipoprotein uptake.

Journal of the Royal Society, Interface·2011
Same author

Acrolein hydrogenation on Pt(211) and Au(211) surfaces: a density functional theory study.

Physical chemistry chemical physics : PCCP·2011
Same author

Anhydrous proton-conducting membrane based on poly-2-vinylpyridinium dihydrogenphosphate for electrochemical applications.

The journal of physical chemistry. B·2011
Same author

Pharmacophore identification, virtual screening and biological evaluation of prenylated flavonoids derivatives as PKB/Akt1 inhibitors.

European journal of medicinal chemistry·2011
Same author

Metabolomic study of insomnia and intervention effects of Suanzaoren decoction using ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry.

Journal of pharmaceutical and biomedical analysis·2011
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

Related Experiment Video

Updated: Mar 2, 2026

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

6.1K

Statistical inference for community detection in signed networks.

Xuehua Zhao1,2, Bo Yang2,3, Xueyan Liu1,2,3

  • 1School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen 518172, China.

Physical Review. E
|May 17, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method for community detection in signed networks. It accurately identifies community structures using a probabilistic model and an automated way to determine the number of communities.

More Related Videos

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.9K
Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
05:30

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

564

Related Experiment Videos

Last Updated: Mar 2, 2026

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

6.1K
Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.9K
Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
05:30

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

564

Area of Science:

  • Network Science
  • Statistical Inference
  • Data Mining

Background:

  • Community detection is a key problem in network science.
  • Signed networks, with positive and negative links, present unique challenges.
  • Existing methods often rely on difficult-to-define heuristics.

Purpose of the Study:

  • To develop a statistically principled method for community detection in signed networks.
  • To accurately identify community structures in signed networks.
  • To automatically determine the number of communities without prior information.

Main Methods:

  • Proposed a probabilistic model for signed networks.
  • Deduced an expectation-maximization-based parameter estimation method.
  • Developed a model selection criterion for automatic community number determination.

Main Results:

  • The proposed method demonstrated superior efficiency and accuracy in detecting communities in both synthetic and real-world signed networks.
  • Experimental results validated the effectiveness of the statistical inference approach.
  • The method outperforms existing techniques in identifying intrinsic community structures.

Conclusions:

  • The presented statistical inference method offers a robust and accurate solution for community detection in signed networks.
  • The approach is mathematically principled and overcomes limitations of heuristic-based methods.
  • The automatic determination of community numbers enhances its practical applicability.