Which measure of central tendency is most likely to be affected by extreme values?

The mean is the measure of central tendency that is most likely to be affected by extreme values, often referred to as outliers. It is calculated by summing all the values in a dataset and dividing by the number of observations. When an extreme value is present, it can significantly alter the total sum, leading to a mean that doesn't accurately reflect the central location of the rest of the data. For instance, in a dataset of salaries where the majority earn between $40,000 and $60,000, but one individual earns $1,000,000, the mean would be skewed upward, misrepresenting the general income level of the majority.

In contrast, the median represents the middle value when the data is ordered and is unaffected by extreme values, making it a more robust measure in the presence of outliers. The mode, which is the most frequently occurring value in a dataset, is also resistant to extreme values, as it only reflects the frequency of occurrence. Standard deviation, while a measure of variability, does not itself represent central tendency; although it can be influenced by extreme values in terms of how it calculates spread, it is not a central measure per se. Therefore, the mean is the measure that best illustrates the impact of