One-Variable Data Distributions
Mean and median both try to describe a data set's 'center' — but they respond very differently to outliers. Drag the outlier below and watch the mean chase after it while the median holds its ground.
The mean (average) adds up every value and divides by the count — every data point, including extreme ones, pulls its full weight. The median is just the middle value once everything’s in order — it only cares about position, not size, so a single huge outlier barely moves it.
That difference is exactly why the mean and median can tell very different stories about the same data. When they’re far apart, that’s a sign of skew: mean noticeably greater than median means a right skew (a few large values stretching the tail up); mean noticeably less than median means a left skew.
Standard deviation measures spread — how far, on average, values sit from the mean. Two data sets can share the exact same mean and median while looking completely different, if one is tightly clustered and the other is spread wide.