The overall average hides 3 different numbers

status splits sensor-telemetry into 3 groups. Here is what humidity_pct looks like inside each.

• fault — mean 42.41, median 42.40 (124 rows)
• warn — mean 41.82, median 41.80 (482 rows)
• ok — mean 40.83, median 40.80 (7,394 rows)

Top to bottom that is 42.41 against 40.83, a spread of 3.9%. The pooled average is 40.91.

select status,
  count(*)                                                  as rows,
  round(avg(humidity_pct)::numeric, 2)                      as mean,
  percentile_cont(0.5) within group (order by humidity_pct) as median
from sensor_telemetry
group by 1
order by mean desc;

The groups are close enough that the pooled average is a fair summary. That is worth confirming rather than assuming: the check costs one query and the failure mode is invisible.

Notice the mean and median columns disagree only slightly here. Always compute both in the group-by. The comparison between them per segment is free and tells you whether you are looking at a level difference or a tail difference.

This is the setup for Simpson's paradox — the case where every segment moves one way and the total moves the other.