I've always wondered how good a 'fit' is the Poisson distribution to the events we observe in reality. Almost always I've seen it be used for modeling occurrence of events. (For example, arrival of cars in a parking garage or the number or messages sent/received by computers hosts on a network etc.)
We usually model such events by the Poisson Distribution. Is the distribution just a good first approximation to how things happen in reality? If I observe the number of cars/day or messages/day in the above two examples and those that are output by 'picking from the distribution' how much do they differ? How good an approximation is Poisson? (Is it an approximation?) What is the 'magic' behind Poisson that it just gets it right (intuitively speaking :)?