Mean vs Median

The mean adds all values and divides by their count. The median is the middle value after sorting, or the average of the two middle values for an even count. Both summarise a typical value, but they respond very differently to extreme data points.

Why it matters

When data is skewed or has outliers, the mean is pulled toward the extremes and can describe nobody in particular. Income, house prices and web response times are classic examples. The median reports what a typical observation looks like, which is why latency is often tracked with the median and percentiles such as p95 and p99 rather than the mean. Showing both, and the gap between them, is a quick check for skew.

Example

Response times (ms): 100, 110, 120, 130, 5000
Mean   = (100+110+120+130+5000) / 5 = 1092 ms
Median = 120 ms

One slow request pushes the mean above every other value, while the median stays representative.

Common mistakes

• Reporting only the mean for skewed data.
• Averaging medians or percentiles from separate groups, which is not valid.
• Forgetting that the mean is useful when you need totals, since mean times count gives the sum.

Related

• Outlier
• Standard deviation
• Histogram
• Latency

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