Which statement best describes the effect of outliers on the mean and the median?

• A. Outliers distort the mean; the median is unaffected by outliers.
• B. Outliers affect the median more than the mean.
• C. Outliers affect only the variance.
• D. Outliers distort the mean; the median is relatively robust to outliers.

Answer: (D)

Outliers pull the average toward them because the mean includes every value in the dataset. A single extreme value can raise or lower the sum enough to move the mean noticeably, even if most data stay the same. The median, by contrast, is the middle value when the data are ordered, so it depends on position rather than the magnitude of extreme values. An extreme observation changes the middle position only if it shifts which values sit in the center, which doesn’t happen as much, especially in larger samples. So, outliers distort the mean while the median remains relatively robust. For example, the dataset 1, 2, 3, 4, 100 has a mean of 22 but a median of 3, illustrating the difference.