it did go on to talk about the uncertainty, especially given the low numbers:
There is a 27% chance that we would observe 3 deaths or less, given an average rate of 4.9 deaths. This is also known as a p-value.5 6Why isn’t our p-value greater? Seems like 27% is quite low. By scientific standards, this isn’t abnormal at all. Observing 3 deaths is completely within reason.
However, the relative uncertainty of our point data is quite large at about 58% (1/sqrt(3)). This is the size of the error. If we were talking about death rates in the thousands, we might have an error of 3% or less. But the reality is that at such low counts, our data is considered quite “fuzzy”.
(I haven't been on over 10 years, but back in the early 2000s there were always rumours about deaths that the organisers managed to ensure ended up categorised as not happening at the event. People who died in ambulances on the way to hospital, or in hospital after injury at the event, or on the road in or out of the event...)
There is a 27% chance that we would observe 3 deaths or less, given an average rate of 4.9 deaths. This is also known as a p-value.5 6Why isn’t our p-value greater? Seems like 27% is quite low. By scientific standards, this isn’t abnormal at all. Observing 3 deaths is completely within reason.
However, the relative uncertainty of our point data is quite large at about 58% (1/sqrt(3)). This is the size of the error. If we were talking about death rates in the thousands, we might have an error of 3% or less. But the reality is that at such low counts, our data is considered quite “fuzzy”.
(I haven't been on over 10 years, but back in the early 2000s there were always rumours about deaths that the organisers managed to ensure ended up categorised as not happening at the event. People who died in ambulances on the way to hospital, or in hospital after injury at the event, or on the road in or out of the event...)