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関連する概念動画

Weighted Mean00:57

Weighted Mean

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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...
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Bias01:22

Bias

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Hindsight Biases01:12

Hindsight Biases

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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? 
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Confirmation Biases01:31

Confirmation Biases

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The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

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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...
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Fundamental Attribution Error01:14

Fundamental Attribution Error

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According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
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Updated: Sep 10, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

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文脈におけるベイジアン確率の重みとして認知バイアス

Bruno Kopp1

  • 1Cognitive Neuropsychology, Department of Neurology, Hannover Medical School, Hannover, Germany.

Frontiers in psychology
|August 22, 2025
PubMed
まとめ
この要約は機械生成です。

保守主義やベースレートの無視のような認知バイアスは 文脈に依存します アダプティブ・ベイジアン・コग्निション (ABC) モデルは,これらのバイアスを不確実性下での意思決定におけるエラーではなく,適応戦略として説明します.

キーワード:
ベイズ推論認知バイアス計算モデル意思決定意思決定支援文脈から学ぶ

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Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

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関連する実験動画

Last Updated: Sep 10, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

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Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

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科学分野:

  • 認知心理学
  • 行動経済学
  • 計算モデリング

背景:

  • 不確実な状況下の人間の判断は 保守主義的偏見やベースレートの無視を含む 系統的な偏見を示します
  • これらのバイアスの文脈依存性の理解は 認知理論と経済理論にとって極めて重要です

研究 の 目的:

  • 人間の確率判断における体系的なバイアスに 課題の文脈がどのように影響するかを調査する.
  • 不確実性下での意思決定における先行確率と証拠可能性の役割を探求する.
  • これらの文脈依存のバイアスを説明する計算モデルを提案し,検証する.

主な方法:

  • 48人の参加者は 主観的な確率判断を必要とする 12つのシナリオを完了しました
  • シナリオは,異なる文脈での証拠可能性 (小世界対大世界) との以前の確率を統合することを含む.
  • 確率論的な情報は確率と相対的な頻度の両方で提示されました.

主要な成果:

  • 任務の文脈は 優先順位と証拠の重さを 大きく左右した.
  • 小規模な世界のシナリオは 先入観を強調することで 保守主義のバイアスを増幅しました
  • 大規模な世界のシナリオは証拠に対する感受性を高め,ベースレートの無視につながり,相対的な頻度はバイアスを軽減しませんでした.

結論:

  • アダプティブ・ベイジアン・コग्निション (ABC) モデルは,コンテキスト,能力の制約,およびメタラーニングの影響を受ける適応戦略として認知バイアスを説明します.
  • 発見は認知心理学,行動経済学,計算モデリングを繋ぎ 不確実な状況下での意思決定を 統一的に理解できるようにしています
  • この研究は,認知バイアスの適応的性質を強調することによって,意思決定支援システムの設計を伝える.