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Implementation of a solver of the generalized birthday problem in Python
Projects for the Intelligent Systems course
In probability theory, the birthday problem concerns the probability that, in a set of n randomly chosen people, some pair of them will have the same birthday. By the pigeonhole principle, the probability reaches 100% when the number of people reaches 366 (since there are 365 possible birthdays, excluding February 29th). It would seem that we would need 183 people (half of 365) to reach a 50% probability. However, 99% probability is reached with just 57 people and 50% probability with just 23 people. These conclusions are based on the assumption that each day of the year (except February 29) is equally probable for a birthday.
Implementation of a solver of the generalized birthday problem in Kotlin
Probability with python - combinations, permutations, sets
This repository contains Python code for exploring two statistical concepts - the birthday problem and the central limit theorem.
Explains the infamous birthday problem and shows how the math indeed checks out
Calculate the probability that at least two people out of n randomly chosen people will share the same birthday
Includes simulations pertaining to Birthday problem, Monty-Hall problem, Bertrand's paradox, Universality of the normal distribution and Bayesian Statistics.