How to model a probability distribution to phone call duration? I was plotting the phone call durations, and the result seems like a right-skewed histogram. Shape-wise,  Poisson, Raylegh, Chi-2 can be candidates for modeling that.
But is there a more rigorous way of modeling? Like a real-world intuition behind one of those options? In addition, how to tune the parameters to fit the curve? Do you know a tool for that? Should I use moments of the distribution?
Any suggestion is welcomed. I have attached the histogram.


It is usually a bad idea to fit a probability density function, bot in the least because the shape and the results would be very sensitive to the choice of the bin size.
Robust and simple options for comparing empirical distribution with parametric ones include QQ-plot (mostly to get the intuitive idea) and the Kolmiogorov-Smirnov test (both based on comparing cdf rather than the pdf.)
