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**probability of event occurring -- poisson distribution?**

I am the keeper of records for my local Volunteer Fire Dept. I have now collected data for each of our incident calls from the last 3 years and have made some _very_ basic stabs at interesting statistics which you can see at:

http://hondovfd.org/statistics.php"

We have about 500 calls a year -- a bit over 40 a month or around 1.3 per day. But as you can see from the graphs at the bottom of that page -- which are just about the full extent of my Excel skills -- they are not randomly distributed over the days of the week or hours of the day. More interesting to all our responders is how they are distributed by number per day. My "Calls per Day" graph seems to show a sorta-exponential decay from 1 per day to 8 (our all time high during a snow storm when our little section of Interstate turned into a Bumper Car arena). However we can go for up to a week with nada, and then break the drought with 3 or 4 in an afternoon.

So the question is: How do I characterize the likely-hood of getting a certain number of calls in any particular day, with the number 0 being of special interest. I think I should be able to compare to a Poisson distribution to see how un-random things are, but my eyes roll into the back of my head about a quarter of the way through the wiki page. Can anyone point me to some other explanations and examples, or have better thoughts on the approach?

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