Why is the median preferred when dealing with skewed data?

The median is preferred when dealing with skewed data because it is not influenced by extreme values, also known as outliers. In a dataset with a significant skew, the presence of these extreme values can greatly affect the mean, leading to a representation of the central tendency that may not accurately reflect the true center of the data distribution.

The median, on the other hand, represents the middle value when all data points are arranged in order. This characteristic makes it a robust measure of central tendency, as it remains stable and reflective of the dataset's typical value, regardless of how extreme the highest or lowest values might be. Therefore, in instances of skewed data, where outliers are present, using the median helps provide a clearer, more reliable insight into the data's central point, making it particularly useful for skewed distributions.