The median is recognized as the most appropriate measure of central tendency when outliers have been removed from a dataset. This is because the median is less influenced by extreme values compared to the mean. When outliers are present, they can significantly skew the mean, making it an unreliable measure of central tendency. The median, on the other hand, is the middle value of a dataset when ordered from least to greatest and remains unaffected by the extremes. Therefore, it provides a better representation of the central location of the data after outliers have been excluded.
References:
* Guidelines for Removing and Handling Outliers in Data1.
* Mean, Median, and Mode: Measures of Central Tendency2.
* Which measure of central tendency should be used when there is an outlier?3.
* How are measures of central tendency affected by outliers?4.