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Define what an outlier is in the context of a dataset's distribution, and describe the two broad categories of sources that can produce these extreme scores in psychological research.
Question: Define what an outlier is in the context of a dataset's distribution, and describe the two broad categories of sources that can produce these extreme scores in psychological research.
Sample answer: An outlier is an extreme score that falls significantly above or below the rest of the scores within a distribution. These extreme values can come from two main sources: they can represent genuine, valid cases on the variable being measured (such as a single clinically depressed person in a happy sample), or they can result from mistakes, such as equipment malfunctions, participant misunderstandings, or researcher errors.
Key points:
- Defines an outlier as an extreme score.
- Notes that outliers fall significantly above or below the rest of the distribution.
- Identifies genuine cases on the measured variable as one source.
- Identifies errors (researcher, participant, or equipment) as another source.
Rubric: The student should correctly define an outlier as an extreme score relative to the rest of the distribution and identify that it can stem from either genuine extreme values on the variable of interest or various forms of error.
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Research Methods in Psychology - 4th American Edition @ KPU
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