What is the measure of central tendency most affected by outliers?

• A. Mean
• B. Median
• C. Mode
• D. Range

Answer: (A)

The central idea is how different measures treat extreme values. The arithmetic mean sums all data points and divides by the count, so every observation, including outliers, affects the result. When an extreme value appears, it adds a large (or small) amount to the total, pulling the average toward itself. That makes the mean highly sensitive to outliers; a single extreme can shift the center noticeably, especially in small to moderately sized data sets.

By contrast, the median is the middle value (or the average of the two middle values). It depends on the order of the data rather than the magnitude of every value, so a single outlier doesn’t move the center much. The mode is the most frequent value, so unless the outlier happens to occur more often than other values, it won’t change the center estimate significantly. The range, while it can change with extreme values, is a measure of spread, not central tendency, so it isn’t describing the center at all.

So, because it uses all data points and is pulled toward an outlier, the mean is the measure most affected by outliers. For example, data like 1, 2, 3, 4, 5, and a very large outlier such as 100 drastically raises the mean while leaving the median near the middle of the bulk data.