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Related Concept Videos

Variation01:19

Variation

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An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
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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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Variability: Analysis01:11

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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus:...
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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
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Taking Rater Exposure to Trainees Into Account When Explaining Rater Variability.

Christy K Boscardin, Marjo Wijnen-Meijer, Olle Ten Cate

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    Summary

    This study introduces a new statistical method to assess rater reliability in graduate medical education, moving beyond simple variability to understand individual rater influence on assessments.

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    Area of Science:

    • Medical Education
    • Statistical Modeling
    • Rater Reliability

    Background:

    • Rater-based judgments are crucial for meaningful assessments in graduate medical education.
    • Existing methods face concerns regarding rater reliability.

    Purpose of the Study:

    • To introduce a statistical modeling technique for assessing rater reliability.
    • To illustrate the utility of this approach using a case example.

    Main Methods:

    • Mixed-effects models were employed to analyze rater and rater role effects.
    • Clinical performance ratings were collected from medical graduates in simulation settings.

    Main Results:

    • Rater role significantly influenced assessments of teamwork and communication skills.
    • Rater variability was partially explained by rater role for other facets of competence.

    Conclusions:

    • A new framework considers raters as idiosyncratic, offering deeper insights than treating them as mere random variability.
    • This approach enhances the understanding of rater influence on assessment scores.