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

The Representativeness Heuristic02:13

The Representativeness Heuristic

17.1K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
17.1K
Hindsight Biases01:12

Hindsight Biases

4.5K
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? 
4.5K
Inductive Reasoning00:59

Inductive Reasoning

69.4K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
69.4K
Deductive Reasoning01:16

Deductive Reasoning

71.7K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
71.7K
The Availability Heuristic01:08

The Availability Heuristic

7.3K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
7.3K
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.9K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.9K

You might also read

Related Articles

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

Sort by
Same author

Healthcare should be accessible for all: development of the ObServation Tool and Resource for Inclusive Communication in Healthcare (OSTRICH).

Disability and rehabilitation·2026
Same author

Comprehensive environmental monitoring and assessment of protected wetland and lake water quality in Croatia and Serbia.

Environmental monitoring and assessment·2020
Same author

Evaluating Sketchiness as a Visual Variable for the Depiction of Qualitative Uncertainty.

IEEE transactions on visualization and computer graphics·2015
Same author

Strong-field plasmonic photoemission in the mid-IR at <1 GW/cm² intensity.

Scientific reports·2015
Same author

Steerable optical tweezers for ultracold atom studies.

Optics letters·2014
Same author

Use of mesenchymal stem cells for cutaneous repair and skin substitute elaboration.

Pathologie-biologie·2014

Related Experiment Video

Updated: Apr 4, 2026

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions
07:09

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Published on: May 2, 2019

6.6K

Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing.

L Micallef1, P Dragicevic, J Fekete

  • 1INRIA and School of Computing, University of Kent, UK. lm304@kent.ac.uk

IEEE Transactions on Visualization and Computer Graphics
|September 11, 2015
PubMed
Summary

Visualizing Bayesian reasoning problems did not improve accuracy in a diverse group, contrary to prior research. Further studies are needed to understand how to best present statistical information to non-experts.

More Related Videos

Investigating the Effect of Visual Imagery and Learning Shape-Audio Regularities on Bouba and Kiki
07:31

Investigating the Effect of Visual Imagery and Learning Shape-Audio Regularities on Bouba and Kiki

Published on: September 13, 2019

10.7K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.8K

Related Experiment Videos

Last Updated: Apr 4, 2026

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions
07:09

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Published on: May 2, 2019

6.6K
Investigating the Effect of Visual Imagery and Learning Shape-Audio Regularities on Bouba and Kiki
07:31

Investigating the Effect of Visual Imagery and Learning Shape-Audio Regularities on Bouba and Kiki

Published on: September 13, 2019

10.7K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.8K

Area of Science:

  • Cognitive Psychology
  • Statistical Reasoning
  • Human-Computer Interaction

Background:

  • Individuals often struggle with statistical information, especially Bayesian reasoning, leading to judgment errors.
  • Previous research indicated that visual representations can aid Bayesian problem comprehension, but evaluations were limited to specific demographics.
  • A need exists to assess diverse populations' understanding of Bayesian problems presented through various formats.

Purpose of the Study:

  • To compare the effectiveness of textual versus six visual representations (Euler diagrams, glyphs, hybrid diagrams) for classic Bayesian problems.
  • To evaluate these representations with a diverse subject pool recruited via crowdsourcing.
  • To investigate the impact of visualization on Bayesian reasoning accuracy across different populations.

Main Methods:

  • Three classic Bayesian reasoning problems were presented using one textual and six distinct visual formats.
  • A diverse group of participants was recruited through crowdsourcing for the primary experiment.
  • A second experiment tested the effect of visualizations when numerical values were omitted from the text.

Main Results:

  • Accuracy in solving Bayesian problems was lower than expected and not significantly improved by any visualization.
  • Visualizations provided no measurable benefit in comprehension or accuracy compared to text alone.
  • Visualizations showed a potential benefit only when accompanying text lacked numerical values.

Conclusions:

  • The study failed to replicate previous findings on the benefits of visual aids for Bayesian reasoning.
  • Simply adding visualizations to textual Bayesian problems offers limited improvement, even with textual references.
  • Future research should focus on heterogeneous, non-expert populations and explore optimal visualization strategies for statistical information.