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

Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

366
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
366
Accuracy, limits, and approximation01:28

Accuracy, limits, and approximation

586
Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
586
Accuracy and Precision01:52

Accuracy and Precision

12.2K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.  Highly accurate...
12.2K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

95.1K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
95.1K
Probability in Statistics01:14

Probability in Statistics

16.5K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
16.5K
Confidence Coefficient01:24

Confidence Coefficient

8.1K
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
8.1K

You might also read

Related Articles

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

Sort by
Same author

Agreements and disagreements with resource-rational contractualism.

The Behavioral and brain sciences·2026
Same author

The Political Psychology of Economic Inequality.

Psychological science in the public interest : a journal of the American Psychological Society·2026
Same author

Levels of analysis for large language models.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

Random generation is what comes to mind in naturalistic settings.

Cognition·2026
Same author

Generated outcomes in risky choice reveal biased sampling and sequential dependencies.

Communications psychology·2026
Same author

Imagining and building wise machines: the centrality of AI metacognition.

Trends in cognitive sciences·2026

Related Experiment Video

Updated: Oct 5, 2025

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

2.6K

Clarifying the relationship between coherence and accuracy in probability judgments.

Jian-Qiao Zhu1, Philip W S Newall2, Joakim Sundh1

  • 1Department of Psychology, University of Warwick, Coventry, United Kingdom.

Cognition
|January 25, 2022
PubMed
Summary

This study reconciles Bayesian intelligence models with empirical data, finding that probabilistic judgment accuracy and coherence increase together, especially with more experience. This suggests heuristics and biases research is relevant after all.

Keywords:
AccuracyCoherenceGamblingRationalitySampling

More Related Videos

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.3K
Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

2.8K

Related Experiment Videos

Last Updated: Oct 5, 2025

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

2.6K
Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.3K
Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

2.8K

Area of Science:

  • Cognitive Science
  • Decision Science
  • Psychology

Background:

  • Bayesian approaches link probability coherence to judgment accuracy.
  • Alternative theories propose accuracy without coherence (ecological rationality).
  • Empirical evidence often supports non-coherent accuracy, challenging Bayesian models.

Purpose of the Study:

  • To investigate the relationship between coherence and accuracy in probabilistic judgments.
  • To reconcile conflicting theoretical claims and empirical findings regarding Bayesian models.
  • To examine how expertise influences the coherence-accuracy link.

Main Methods:

  • A high-power experiment using poker probability judgments and an analogous urn task.
  • Involving participants with varying levels of poker expertise (novices, occasional players, experts).
  • Analyzing the relationship between coherence and accuracy across groups and individuals.

Main Results:

  • A significant positive relationship was found between coherence and accuracy.
  • This relationship held both between different expertise groups and within individuals.
  • A sample-based Bayesian approximation model explained both positive findings and previous null results.

Conclusions:

  • Coherence and accuracy in probabilistic judgments are positively related, contrary to some theories.
  • Expertise enhances both coherence and accuracy, supporting a nuanced view of Bayesian models.
  • The findings reconcile theoretical expectations with empirical data, reaffirming the relevance of coherence in judgment accuracy.