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In probability theory, the birthday problem asks for the probability that, in a set of n randomly chosen people, at least two will share the same birthday. The birthday paradox is the counterintuitive fact that only 23 people are needed for that probability to exceed 50%.
A birthday attack is a bruteforce collision attack that exploits the mathematics behind the birthday problem in probability theory. This attack can be used to abuse communication between two or more parties. The attack depends on the higher likelihood of collisions found between random attack attempts and a fixed degree of permutations ...
(1/365! is the probability that you take 365 people with distinct birthdays and, picking them one at a time, correctly pick them in birthday order). Let's work with smaller numbers: assume a 3-sided coin (it's more interesting than a two-sided, but the numbers are small).
Usually, coincidences are chance events with underestimated probability. [3] An example is the birthday problem, which shows that the probability of two persons having the same birthday already exceeds 50% in a group of only 23 persons. [4] Generalizations of the birthday problem are a key tool used for mathematically modelling coincidences. [5]
A life table (or a mortality table) is a mathematical construction that shows the number of people alive (based on the assumptions used to build the table) at a given age. In addition to the number of lives remaining at each age, a mortality table typically provides various probabilities associated with the development of these values.
English: In probability theory, the birthday paradox 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 367 (since there are 366 possible birthdays, including February 29). However, 99% ...
The probability is sometimes written to distinguish it from other functions and measure P to avoid having to define "P is a probability" and () is short for ({: ()}), where is the event space, is a random variable that is a function of (i.e., it depends upon ), and is some outcome of interest within the domain specified by (say, a particular ...
We assume equal probability that either is a boy or a girl. The three discernible cases are thus: both are girls (GG) – with probability P(GG) = 1 / 4 , both are boys (BB) – with probability of P(BB) = 1 / 4 , and; one of each (G·B) – with probability of P(G·B) = 1 / 2 . These are the prior probabilities.