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Two urns containing white and red balls. In probability and statistics, an urn problem is an idealized mental exercise in which some objects of real interest (such as atoms, people, cars, etc.) are represented as colored balls in an urn or other container.
In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws, without replacement, from a finite population of size that contains exactly objects with that feature, wherein each draw is either a success or a failure.
In the mathematics of shuffling playing cards, the Gilbert–Shannon–Reeds model is a probability distribution on riffle shuffle permutations. [1] It forms the basis for a recommendation that a deck of cards should be riffled seven times in order to thoroughly randomize it. [ 2 ]
In probability theory, the rule of succession is a formula introduced in the 18th century by Pierre-Simon Laplace in the course of treating the sunrise problem. [1] The formula is still used, particularly to estimate underlying probabilities when there are few observations or events that have not been observed to occur at all in (finite) sample data.
2.1×10 −2: Probability of being dealt a three of a kind in poker 2.3×10 −2: Gaussian distribution: probability of a value being more than 2 standard deviations from the mean on a specific side [17] 2.7×10 −2: Probability of winning any prize in the Powerball with one ticket in 2006 3.3×10 −2: Probability of a human giving birth to ...
Then the set X = {{x 1, y 1}, {x 2, y 2}, {x 3, y 3}, ...} can be in the model but sets such as {x 1, x 2, x 3, ...} cannot, and thus X cannot have a choice function. In 1938, [ 19 ] Kurt Gödel showed that the negation of the axiom of choice is not a theorem of ZF by constructing an inner model (the constructible universe ) that satisfies ZFC ...
Banach's match problem is a classic problem in probability attributed to Stefan Banach.Feller [1] says that the problem was inspired by a humorous reference to Banach's smoking habit in a speech honouring him by Hugo Steinhaus, but that it was not Banach who set the problem or provided an answer.
Let n be very large and consider a random graph G on n vertices, where every edge in G exists with probability p = n 1/g −1. We show that with positive probability, G satisfies the following two properties: Property 1. G contains at most n/2 cycles of length less than g. Proof. Let X be the number cycles of length less than g.