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

Modeling in Therapy01:26

Modeling in Therapy

164
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
164
What are Estimates?01:06

What are Estimates?

5.5K
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
5.5K
Group Design02:01

Group Design

9.8K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
9.8K
Trimmed Mean01:10

Trimmed Mean

3.0K
While measuring the mean of a data set, care needs to be taken when associating the mean to its central tendency. The same goes for the arithmetic mean, the geometric mean, or the harmonic mean. This is because the presence of a single outlier data value can significantly affect the mean. That is, the mean is sensitive to fluctuations in the data set.
Although certain measures of central tendency are not sensitive to outliers, there are alternative versions of the mean that get around the...
3.0K
Regression Toward the Mean01:52

Regression Toward the Mean

6.5K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.5K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

95
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
95

You might also read

Related Articles

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

Sort by
Same author

A Convergence of Theories of Mind and Brain.

Computational brain & behavior·2026
Same author

Association of triglyceride-cholesterol-body weight index with in-hospital mortality in critically ill patients with heart failure.

Scientific reports·2026
Same author

Triple-interlocked-nanotwinned bulk magnesium alloys with exceptional strength and ageing resistance.

Nature communications·2026
Same author

Set-shifting and task-switching make differential contributions to divergent thinking in adolescence.

BMC psychology·2026
Same author

Deep learning-guided discovery and engineering of binding peptides for accelerated enzymatic degradation of polyethylene terephthalate.

Trends in biotechnology·2026
Same author

Grain-Boundary-Free Fusion of Non-Oriented Nanocrystals via Transient Amorphization.

Small (Weinheim an der Bergstrasse, Germany)·2026

Related Experiment Video

Updated: Oct 2, 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

Modeling mean estimation tasks in within-trial and across-trial contexts.

Ke Tong1, Chad Dubé2

  • 1Nanyang Technological University, Singapore, Singapore. ke.tong@ntu.edu.sg.

Attention, Perception & Psychophysics
|February 24, 2022
PubMed
Summary

This study introduces the Fidelity-based Integration Model (FIM) to explain how people estimate mean values. FIM accurately simulates human performance in mean estimation tasks, unlike other models.

Keywords:
Implicit/explicit memoryMemory: Visual working and short-term memoryVisual perception

More Related Videos

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.0K
A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

4.7K

Related Experiment Videos

Last Updated: Oct 2, 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
The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.0K
A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

4.7K

Area of Science:

  • Cognitive psychology
  • Computational neuroscience
  • Visual perception

Background:

  • Mean estimation is crucial for ensemble coding and cue integration.
  • Understanding information summarization in perception is key.

Purpose of the Study:

  • To formalize information summarization in mean estimation using computational models.
  • To compare the predictive power of the Fidelity-based Integration Model (FIM) against other models.
  • To investigate within-trial weight distribution, across-trial integration, and set-size effects.

Main Methods:

  • Development and comparison of computational models, including FIM.
  • Experimental investigation of mean estimation tasks (sequential and simultaneous).
  • Analysis of observer behavior regarding trial weighting and estimation biases.

Main Results:

  • Observed non-equal weighting within trials and biases in over/underestimation of means.
  • Demonstrated declining and stabilizing mean estimation accuracy with increasing set sizes.
  • FIM successfully simulated all experimental patterns, while other models failed.

Conclusions:

  • FIM provides a robust framework for understanding information processing in mean estimation.
  • FIM's structure offers insights into visual working memory capacity and sub-sampling.
  • FIM facilitates task-dependent modeling for ensemble coding research and synthesis.