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

Causality in Epidemiology01:21

Causality in Epidemiology

882
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
882
Cause and Effect01:53

Cause and Effect

11.4K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
11.4K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

160
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
160
Hindsight Biases01:12

Hindsight Biases

3.9K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
3.9K
Correlation and Causation01:27

Correlation and Causation

39.6K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
39.6K
Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

10.1K
The actual hypothesis testing begins by considering two hypotheses. They are termed  the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As  a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
10.1K

You might also read

Related Articles

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

Sort by
Same author

TiVy: Time Series Visual Summary for Scalable Visualization.

IEEE transactions on visualization and computer graphics·2025
Same author

Visagreement: Visualizing and Exploring Explanations (Dis)Agreement.

IEEE transactions on visualization and computer graphics·2025
Same author

ZigzagNetVis: Suggesting Temporal Resolutions for Graph Visualization Using Zigzag Persistence.

IEEE transactions on visualization and computer graphics·2025
Same author

TopoMap++: A Faster and More Space Efficient Technique to Compute Projections with Topological Guarantees.

IEEE transactions on visualization and computer graphics·2024
Same author

MOUNTAINEER: Topology-Driven Visual Analytics for Comparing Local Explanations.

IEEE transactions on visualization and computer graphics·2024
Same author

MoReVis: A Visual Summary for Spatiotemporal Moving Regions.

IEEE transactions on visualization and computer graphics·2023
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Sep 16, 2025

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

8.6K

CounterCrime - Using Counterfactual Explanations to Explore Crime Reduction Scenarios.

Marcos M Raimundo, Germain Garcia-Zanabria, Luis Gustavo Nonato

    IEEE Transactions on Visualization and Computer Graphics
    |July 11, 2025
    PubMed
    Summary
    This summary is machine-generated.

    CounterCrime, a visual analytics tool, uses counterfactual explanations to explore "what-if" scenarios for crime reduction. It helps policymakers identify key variables to make urban regions safer by analyzing socioeconomic and urban data.

    More Related Videos

    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
    09:49

    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

    Published on: December 24, 2015

    14.3K
    The Modified Temptation Resistance Task: A Paradigm to Elicit Children's Strategic Lie-telling
    06:51

    The Modified Temptation Resistance Task: A Paradigm to Elicit Children's Strategic Lie-telling

    Published on: April 6, 2018

    8.5K

    Related Experiment Videos

    Last Updated: Sep 16, 2025

    An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
    07:36

    An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

    Published on: May 3, 2016

    8.6K
    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
    09:49

    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

    Published on: December 24, 2015

    14.3K
    The Modified Temptation Resistance Task: A Paradigm to Elicit Children's Strategic Lie-telling
    06:51

    The Modified Temptation Resistance Task: A Paradigm to Elicit Children's Strategic Lie-telling

    Published on: April 6, 2018

    8.5K

    Area of Science:

    • Data Science
    • Urban Planning
    • Criminology

    Background:

    • Crime analysis is complex, influenced by socioeconomic and urban factors.
    • Understanding these impacts is crucial for effective public policy and crime mitigation.
    • Counterfactual explanations offer a way to explore hypothetical scenarios for crime reduction.

    Purpose of the Study:

    • To introduce CounterCrime, a visual analytics tool for crime analysis.
    • To leverage counterfactual explanations for generating "what-if" crime scenarios.
    • To aid decision-makers in understanding and mitigating regional crime rates.

    Main Methods:

    • Developed CounterCrime, a visual analytics tool with interactive metaphors.
    • Organized analysis across city, region group, and regional levels.
    • Employed a greedy strategy for variable selection and similarity grouping for counterfactuals.

    Main Results:

    • The tool facilitates exploration of counterfactual scenarios at multiple granularities.
    • Identified key variables influencing crime rates and recommended them for intervention.
    • Validated findings using crime data from São Paulo, Brazil, through case studies.

    Conclusions:

    • CounterCrime offers a novel perspective on crime analysis through "what-if" scenario exploration.
    • The tool can anticipate changes to improve regional safety and inform policy.
    • Context-specific interventions are necessary, as effective scenarios may vary between regions.