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

Weighted Mean00:57

Weighted Mean

5.2K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.2K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

7.7K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
7.7K
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
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...
6.3K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

8.3K
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
8.3K
Central Tendency: Analysis01:10

Central Tendency: Analysis

153
Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
153
Arithmetic Mean01:08

Arithmetic Mean

14.1K
The arithmetic mean is the most commonly used measure of the central tendency of a data set. It is defined as the sum of all the elements constituting the data set, divided by the total number of elements. It is sometimes loosely referred to as the “average.”
When all the values in a data set are not unique, the sum in the numerator can be calculated by multiplying each distinct value by its frequency.
Sometimes, the arithmetic mean of a sample can be affected by a few data points...
14.1K

You might also read

Related Articles

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

Sort by
Same author

Okra eyelid patch versus sodium hyaluronate combined with ofloxacin eye drop in the treatment of meibomian gland dysfunction: a randomized controlled trial.

BMC ophthalmology·2026
Same author

Effects of Replacing Oat Hay with Peanut Hull Depolymerization Product on Growth Performance, Serum Biochemical Parameters, and Rumen Fermentation in Holstein Dairy Bulls.

Animals : an open access journal from MDPI·2026
Same author

Excitotoxicity and PANoptosis are examined through endoplasmic reticulum stress of brain in the fat greenling (Hexagrammos otakii) under hypoxic stress.

Fish & shellfish immunology·2026
Same author

HMGB3 facilitates malignant phenotype of esophageal carcinoma via histone lactylation- and Wnt/β-catenin-dependent transcription activation of c-myc.

NPJ precision oncology·2026
Same author

Comprehensive management of hemodialysis catheter-related bloodstream infections: a narrative review.

Frontiers in cellular and infection microbiology·2026
Same author

Sustainable energy harvesting <i>via</i> a scalable Janus photonic metamaterial for thermoelectric generation.

Materials horizons·2026
Same journal

Mind wandering during first- and foreign-language reading.

Psychonomic bulletin & review·2026
Same journal

Lexical word processing is unaffected by rapid invisible frequency tagging in reading: Evidence from eye movements.

Psychonomic bulletin & review·2026
Same journal

Anxiety modulates voluntary attentional orienting to emotional gaze cues: Eye movements for pro- and anti-saccades.

Psychonomic bulletin & review·2026
Same journal

Faster key-press responses to front vowels than back vowels when matching heard vowels with represented vowels.

Psychonomic bulletin & review·2026
Same journal

Testing the interleaving effect without response bias: A forced-choice reevaluation of Kornell and Bjork (2008).

Psychonomic bulletin & review·2026
Same journal

The impact of social interaction on abstract concepts.

Psychonomic bulletin & review·2026
See all related articles

Related Experiment Video

Updated: Jul 4, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.3K

Seeing in crowds: Averaging first, then max.

Xincheng Lu1, Ruijie Jiang1, Meng Song1

  • 1Department of Psychology, School of Social Sciences, Tsinghua University, Room 506, Weiqing Building, Beijing, 100084, People's Republic of China.

Psychonomic Bulletin & Review
|February 10, 2024
PubMed
Summary
This summary is machine-generated.

Object recognition is limited by crowding, where peripheral vision integrates nearby items. Our study reveals visual processing uses a "max" strategy, not averaging, to select the strongest response, improving object recognition.

Keywords:
CrowdingPoolingPsychophysicsVision

More Related Videos

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

2.5K
Averaging of Viral Envelope Glycoprotein Spikes from Electron Cryotomography Reconstructions using Jsubtomo
08:29

Averaging of Viral Envelope Glycoprotein Spikes from Electron Cryotomography Reconstructions using Jsubtomo

Published on: October 21, 2014

12.2K

Related Experiment Videos

Last Updated: Jul 4, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.3K
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

2.5K
Averaging of Viral Envelope Glycoprotein Spikes from Electron Cryotomography Reconstructions using Jsubtomo
08:29

Averaging of Viral Envelope Glycoprotein Spikes from Electron Cryotomography Reconstructions using Jsubtomo

Published on: October 21, 2014

12.2K

Area of Science:

  • Visual perception
  • Cognitive neuroscience
  • Computational vision

Background:

  • Crowding limits object recognition by excessive integration in peripheral vision.
  • Understanding pooling mechanisms in visual processing is crucial.

Purpose of the Study:

  • To investigate the pooling mechanisms underlying visual crowding.
  • To determine how the brain processes information from multiple items in peripheral vision.

Main Methods:

  • Measured internal response distributions in an orientation crowding task.
  • Developed a computational model combining averaging and signed-max operations.

Main Results:

  • Observed a pattern suggesting a "max" operation, not averaging, for perceptual judgment.
  • A model with first-stage averaging and second-stage signed-max predicted human errors.
  • Diverse errors were predicted across various signal strengths.

Conclusions:

  • Visual processing employs distinct pooling strategies at different stages.
  • Early visual processing may involve linear averaging, while later stages use nonlinear "max" operations.
  • This combination of strategies resolves bottlenecks in visual information processing.