I am interested in learning if there has been published some type of code or package that can help me with the following problem:
An event takes place 30 times.
Each event can return 6 different values (0,1,2,3,4,5), each with their own unique probability.
I would like to estimate the probability of the total values -after all the scenarios have been simulated - is above X (e.g. 24).
The issue I have is that I can't - in a given event where the value is 3- multiply the probability of value 3*3 and add it together with the previous obtained values. Instead I need to simulate every single variation that is possible.
Is there any relatively simple solution to solve this issue?
First of all, what you're describing isn't scenario analysis. That said, Python can be used to estimate complex probabilities where an analytical solution might be hard or impossible to find.
Assuming an event takes place 30 times, with outcomes [0,1,2,3,4,5], and each outcome has a probability of occurring given by the list (for example) p = [.1,.2,.2,.3,.1,.1], you can approximate the probability that the sum of all 30 events is greater than X with
import numpy as np
X = 80
np.mean([sum(np.random.choice(a=[0,1,2,3,4,5], size= 30,p=[.1,.2,.2,.3,.1,.1])) > X for i in range(10000)])
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