Let's say for example that you want to get a fresh cut. I am eeger to know how could one calculate probability that barbershop will be full? What are the parameters that should be looked. I don't need anything concrete, just wanted to know what are the possible approaches? I was thinking of maybe Poisson stochastic process, but I think it doesn't fully fit the story.
2026-03-29 18:32:47.1774809167
How to calculate probability that I will encounter full barbershop when I go for a cut?
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First of all, you would have to define a sample of possible barbershops. Maybe calculate the number of barbershops within walking distance. You would also need to specify the maximum waiting time you would be willing to wait. Then I would suggest a calculating the probability that a barbershop will be full given a whole range of other parameters such as:
Then you could add more parameters such as the hour of the day for your search and operation hours of a barbershop. I am sure that they do not have the same load during let's say 8a.m. and 16:00. Also this could be done for different days of the week (e.g. Saturday vs Tuesday).
I would also look to somehow model a barbershop's popularity into my calculations. But if we take for granted that supply and demand for barbershops has reached an equilibrium this might not be necessary.
You could also use a Bayesian approach where as you update the aforementioned model with observations.