first_response_min: mean 155, median 83

A number worth keeping: on support-tickets, first_response_min has a mean of 155 and a median of 83.

The mean is 155. The median is 83. That is a gap of 86.3%, and it is not noise — the p90 is 355 and the max is 4,444, so the top of the distribution is dragging the average somewhere a minority of rows actually live.

select
  avg(first_response_min)                                                     as mean,
  percentile_cont(0.5) within group (order by first_response_min)             as median,
  percentile_cont(0.9) within group (order by first_response_min)             as p90,
  max(first_response_min)                                                     as max
from support_tickets;

The practical consequence is that "average first response min" answers a question nobody asked. If someone wants to know what a typical row looks like, the median answers it. If someone is forecasting a total, the mean is the right tool and the skew does not matter, because the mean times the count is the total.

So the rule is not "never use the mean". It is: name which question you are answering, then pick the statistic that answers it. A report that shows 155 with no median next to it has quietly decided you meant the first question.

There is a longer version of this in Describing a column without lying, and the pattern is the short one.