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

Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Biostatistics: Overview01:20

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Statistical Significance01:37

Statistical Significance

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...
Chi-square Analysis02:46

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
Study Design in Statistics01:15

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...

You might also read

Related Articles

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

Sort by
Same author

Post-stroke rehabilitation in inflammatory rheumatic diseases: outcome measures, digital tools, and patient education perspectives.

Rheumatology international·2026
Same author

Artificial intelligence in rheumatology: a cross-sectional Scopus-based analysis.

Rheumatology international·2026
Same author

Publication and Retraction Activity in the Field of Extracorporeal Membrane Oxygenation: Origins, Concerns, and Perspectives.

Journal of Korean medical science·2026
Same author

Evaluating Large Language Models for Post-Publication Promotion: A Blinded Comparative Study of Social Media Posts in Public Health.

Journal of Korean medical science·2026
Same author

Healthcare professionals' knowledge and views on unmet needs in prevention of infectious comorbidities in pregnant women with inflammatory rheumatic diseases.

Rheumatology international·2026
Same author

Handgrip strength as a valuable multidimensional clinical parameter: a cross-sectional Scopus-based analysis.

Rheumatology international·2026

Related Experiment Video

Updated: Jul 2, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Retracted Publications Related to Statistics: A Scopus-Based Bibliometric Analysis.

Aizhan Oralbek1, Marlen Yessirkepov2,3, Olena Zimba4,5,6

  • 1Department of Social Health Insurance and Public Health, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.

Journal of Korean Medical Science
|July 1, 2026
PubMed
Summary

The number of retracted statistics publications has significantly increased, highlighting issues in scientific publishing. This trend underscores the need for enhanced statistical expertise and ethical training in research.

Keywords:
BibliometricsEthicsRetraction of Publication as TopicStatistical StudiesStatisticsStatistics as Topic

Related Experiment Videos

Last Updated: Jul 2, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Area of Science:

  • Bibliometrics
  • Scientific Publishing
  • Statistics

Background:

  • Statistics is fundamental to scientific research, encompassing data collection, analysis, and interpretation.
  • Publication retractions signify serious scientific concerns, necessitating analysis to identify ethical and structural flaws.
  • Analyzing retractions aids in understanding and improving the integrity of scientific literature.

Purpose of the Study:

  • To conduct a bibliometric and descriptive analysis of retracted publications associated with the keyword 'statistics'.
  • To identify trends, geographical origins, journals, and primary reasons for retractions in statistics-related research.
  • To assess the temporal dynamics of retractions in this field.

Main Methods:

  • Bibliometric and descriptive analysis of 680 retracted papers from the Scopus database (search date: August 18, 2025).
  • Analysis included year, country, journal, keywords, and retraction reasons, with collaboration networks visualized using VOSviewer.
  • Retraction reasons were cross-verified with the Retraction Watch Database; temporal trends were analyzed using linear regression.

Main Results:

  • A significant upward trend in retractions was observed between 2006 and 2025 (P = 0.030).
  • China (n=426), India (n=67), and the United States (n=49) were the leading countries for retractions.
  • Top retraction reasons included journal/publisher investigations (n=297), unreliable results (n=189), and referencing issues (n=153).

Conclusions:

  • The rise in retracted statistics publications reflects improved oversight and ethical awareness.
  • Enhancing statistical expertise in peer review and improving authors' statistical literacy are crucial.
  • Implementing robust training and mentoring programs is vital to prevent future ethical violations in scientific publishing.