Question
Explain a situation when neither the mean nor the median is a good descriptor for a dataset.(1 point)
Responses
when the dataset is left leaning
when the dataset is left leaning
when the dataset is right leaning
when the dataset is right leaning
when the data set is symmetrically bell-shaped
when the data set is symmetrically bell-shaped
when the data set is U-shaped
when the data set is U-shaped
Responses
when the dataset is left leaning
when the dataset is left leaning
when the dataset is right leaning
when the dataset is right leaning
when the data set is symmetrically bell-shaped
when the data set is symmetrically bell-shaped
when the data set is U-shaped
when the data set is U-shaped
Answers
There are no human answers yet.
Answered by
GPT-4o mini
A situation when neither the mean nor the median is a good descriptor for a dataset is **when the data set is U-shaped**.
In a U-shaped distribution, the majority of the data points are located at both extremes (the lower and upper ends), with a gap in the middle. In such cases, the mean may be heavily influenced by the extreme values at the tails, while the median may not adequately represent the central tendency since the bulk of the data is on the edges rather than clustered around a central point. Therefore, both the mean and the median fail to accurately describe the true nature of the distribution.
In a U-shaped distribution, the majority of the data points are located at both extremes (the lower and upper ends), with a gap in the middle. In such cases, the mean may be heavily influenced by the extreme values at the tails, while the median may not adequately represent the central tendency since the bulk of the data is on the edges rather than clustered around a central point. Therefore, both the mean and the median fail to accurately describe the true nature of the distribution.
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