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Which measure best describes the central tendency in a negatively skewed distribution?

  1. Mean

  2. Median

  3. Mode

  4. Range

The correct answer is: Median

In a negatively skewed distribution, the bulk of the data points tend to cluster to the right of the distribution, with a long tail extending to the left. This impacts the central tendency measures quite significantly. The median is the most appropriate measure for central tendency in this context because it represents the middle value when the data points are arranged in order. Unlike the mean, which can be influenced by extreme values in the tail (which are lower in a negatively skewed distribution), the median remains stable and provides a more accurate reflection of the central location of the data. The mode is not as useful in this situation because, while it indicates the most frequently occurring value, it does not account for the overall distribution shape or the central clustering of data points. The range, which measures the spread of the data from the lowest to the highest value, does not describe central tendency but rather the dispersion of the dataset. Therefore, the median is the best measure for central tendency in a negatively skewed distribution, as it accurately captures the central point around which the majority of the data is positioned.