Upvoting because this is one of the most common misconceptions around performance I encounter. You have received several good responses already, and I'll add j

Upvoting because this is one of the most common misconceptions around performance I encounter. You have received several good responses already, and I'll add just one more: the latency distribution of many software systems is in practise closer to a power law than a normal distribution. This means the "outliers" dominate almost all ways to look at the distribution, which means you will find the very high percentiles (including max) to be more informative of what going on (on a per-request basis) than the lower percentiles. Another feature of power laws is that it's hard to estimate their shape based on the central values -- one of the more effective methods is to MLE fit a tail exponent to the tail (i.e. what's beyond the 95th percentile) and then extrapolate from that also to central values when necessary. This yields a less biased estimate of the mean, for example.