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Explanation: The median is the most robust measure of central tendency for skewed distributions because it represents the middle value when data is ordered, unaffected by extreme values. Unlike the mean, which can be disproportionately influenced by outliers, the median provides a more accurate representation of the dataset's central point in such cases. For example, in income distributions where a few individuals earn significantly more than others, the median reflects the typical earning level better than the mean. Option A: The mean is sensitive to outliers and fails to represent the central tendency accurately in skewed distributions. Option C: While the mode indicates the most frequent value, it is less informative in representing the dataset's overall central tendency. Option D: Standard deviation measures variability, not central tendency. Option E: Range only highlights the spread between maximum and minimum values, providing no insight into central tendency.
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