What is the probability a person sees a tree by looking out of the window? I'm familiar with the basic probability rules which problems come in the form of:

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*What is the probability of getting a head next by tossing a coin? 0.5

*What is the probability of getting a 3 if a number is chosen uniformly at random from the set {1, 2, 3, 4}? 0.25

How more complicated forms of questions are calculated? for example: what is the probability a person sees a tree by looking out of the window given there are 2 trees that could be seen from that window?
There are many things to consider:

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*The person's eye vision.

*Time of the day (and how many light bulbs are around in case it's after sunset)

*The direction at which he looks.

*How tall are the trees?

*Can the person pass a drug test at the given moment?

*Does he have a history of delusions?

And the list goes on which may contain infinite possibilities leading to seeing / not seeing a tree. Given we don't have a frequency of people who saw a tree by looking from that very same window, how to calculate the probability with any degrees of accuracy? How confident are we given that we are 100% confident the probability of getting 3 out of {1, 2, 3, 4} is 0.25? What if we don't have anything given in which case the question is the same as the title?


How to calculate the probability with any degrees of accuracy??

There is no way to compute this because the estimates that we make to perform the computation have an undefined accuracy due to lack of knowledge.
The way that it is generally tackled is that we use some simplified model and apply it to the problem. But the model is wrong and we have no way to express how wrong exactly. Still, as long as the range of error is small, or smaller than the statistical variations, then the model is good enough to apply.
See also: https://en.m.wikipedia.org/wiki/All_models_are_wrong
