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相关概念视频

The Representativeness Heuristic02:13

The Representativeness Heuristic

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The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
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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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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
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Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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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: Jun 4, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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从缺少的数据到有信息的GPA预测:通过部分识别方法导航选择过程的信念.

Eduardo Alarcón-Bustamante1,2,3,4, Jorge González3,4,5, David Torres Irribarra1,3,4

  • 1Escuela de Psicología, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile.

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概括

从招生考试成绩中预测大学GPA是具有挑战性的,因为对于未被选择的申请人缺乏数据. 这项研究使用了部分识别理论和较温和的假设来改进招生数据的回归分析.

关键词:
学术表现预测学术表现预测可忽略的不可忽视性有关信息的假设.随机失踪的人是随机失踪的人.预测有效性 预测有效性

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科学领域:

  • 教育测量教育的测量
  • 统计 统计 统计 统计
  • 高等教育 高等教育

背景情况:

  • 预测有效性研究通常使用回归分析来评估大学入学考试成绩预测大学GPA的能力.
  • 一个关键的挑战是缺少数据的问题:所有申请人的考试成绩都可用,但只有被录取的学生才能观察到GPA.

研究的目的:

  • 提出一种替代方法来处理大学招生预测有效性研究中缺少的数据.
  • 探索结果如何根据对选择过程的假设而有所不同.

主要方法:

  • 利用部分可识别性的理论来解决回归分析中缺失的数据.
  • 与标准方法相比,应用了较温和的假设,而标准方法需要强有力的假设来识别数据.

主要成果:

  • 证明回归分析的结果可以根据所采用的关于入学选择过程的假设有显著差异.
  • 展示了使用大学招生数据集的部分识别方法的应用.

结论:

  • 部分可识别性理论提供了一个灵活的框架,用于根据各种假设集分析大学招生中的预测有效性.
  • 强调在评估招生考试的预测能力时仔细考虑和说明假设的重要性.