>  I've not seen them described that way in the road safety literature that I'm 
> familiar with. How would that work? If the number of accidents is on the Y 
> axis, what variable would the X axis have? If we go with road accidents (my 
> field of expertise) it can't be age/driving experience, because the accident 
> stats in NO way form a poisson distribution  when age/experience is your 
> X-axis variable. (Actually, road prangs by age/experience gives you more of a 
> U-shaped curve.) Also, rate of accidents (be they road prangs or glider 
> prangs) aren't constant over time (as required for a poisson distribution to 
> be your distribution of
choice) - they vary by time of day, for fairly obvious reasons, as well as 
other things (day of the week, long weekends, etc etc).

> You appear to be approaching the issue from a rather different statistical 
> approach to the ones I'm familiar with. Could you spell out your 
> approach/methods in more detail? It's always interesting to hear how folk in 
> other fields approach problems I'm familiar with. :-)

I am approaching it as counting events occurring over a duration of time 
(analogous to say counting disintegrations per second for radioactive decay).

Y axis would be the accident rate with any metric that you care to choose (i.e. 
accidents per 1,000 hours flown, accidents per 100km travelled, accidents per 
1,000 flights etc.).
Y axis would be a duration of time, i.e over one year, over 10 years, over 100 
years.

Then it is a case of using the appropriate test to compare the two groups (null 
hypothesis being that the accident rate between two groups is the same).

A fairly blunt measure granted.

Given your experience with road accidents analysis, how would you approach it?
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