Which measure of central tendency is most appropriate for skewed distributions with outliers?

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Multiple Choice

Which measure of central tendency is most appropriate for skewed distributions with outliers?

When a distribution is skewed and contains outliers, the median is the most reliable way to describe a typical value. The median is the middle value when data are ordered (or the average of the two middle values when the sample size is even), so it doesn’t get dragged toward extreme scores like the arithmetic mean does. For example, in a skewed income distribution where a few very high earners pull the average up, the median stays near the center of the main group of data and better reflects a typical person's earnings. The mean, by contrast, uses every value and is sensitive to outliers, which can be misleading in skewed data. The mode can be uninformative for continuous data and doesn’t necessarily represent a central location. The geometric mean is useful for products or growth rates but is not robust to outliers and isn’t appropriate for all data types. So the median best captures the central tendency when skew and outliers are present.

Which measure of central tendency is most appropriate for skewed distributions with outliers?

Study for the Psychology Statistics Test. Engage with interactive quizzes and detailed explanations. Equip yourself with the skills and confidence to succeed!

Which measure of central tendency is most appropriate for skewed distributions with outliers?

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