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Related Concept Videos

Statistical Significance01:37

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
Regression Toward the Mean01:52

Regression Toward the Mean

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 researchers try to extrapolate results...
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Unusual Results

Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
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Testing a Claim about Population Proportion

A complete procedure for testing a claim about a population proportion is provided here.
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Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...

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Updated: Jun 28, 2026

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

Statistical processing: not so implausible after all.

Sang Chul Chong1, Sung Jun Joo, Tatiana-Aloi Emmanouil

  • 1Department of Psychology, Yonsei University, 262 Seongsanno, Seodaemun-gu, Seoul 120-749, Korea. scchong@yonsei.ac.kr

Perception & Psychophysics
|October 18, 2008
PubMed
Summary
This summary is machine-generated.

Statistical mode of perceptual processing may not rely on focused attention. New findings suggest distributed attention to stimuli sets better explains statistical processing, challenging prior focused attention claims.

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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

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Last Updated: Jun 28, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

Area of Science:

  • Cognitive Psychology
  • Visual Perception

Background:

  • Challenging the notion that statistical processing in perception relies solely on focused attention to small samples.
  • Investigating alternative explanations for perceptual statistical learning.

Discussion:

  • Experimental results contradict the focused attention hypothesis by showing no performance difference between blocked and randomly mixed conditions.
  • Participants exhibited impaired performance in estimating mean size with small samples compared to the full display, questioning focused attention strategies.
  • Evidence suggests participants did not employ the proposed focused attention strategy of comparing largest items.

Key Insights:

  • Findings question the Myczek and Simons (2008) claim that focused attention explains statistical perceptual processing.
  • Distributed attention to sets of similar stimuli provides a more coherent explanation for observed phenomena.
  • Statistical processing in perception is better accounted for by distributed attention mechanisms.

Outlook:

  • Further research is needed to fully elucidate the role of attention in statistical perceptual learning.
  • Exploring the neural mechanisms underlying distributed attention in statistical processing.
  • Investigating the generalizability of these findings across different perceptual tasks and stimuli.