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Bob wants to guess the maximal number with the highest possible probability, while Alice's goal is to keep this probability as low as possible. The difference with the basic secretary problem are two: Alice does not have to write numbers uniformly at random. She may write them according to any joint probability distribution to trick Bob.
This list contains only probabilists in the sense of mathematicians specializing in probability theory. David Aldous (born 1952) Siva Athreya (born 1971) Thomas Bayes (1702–1761) - British mathematician and Presbyterian minister, known for Bayes' theorem; Gerard Ben-Arous (born 1957) - Courant Institute of Mathematical Sciences; Itai Benjamini
The probability of this happening is 1 in 13,983,816. The chance of winning can be demonstrated as follows: The first number drawn has a 1 in 49 chance of matching. When the draw comes to the second number, there are now only 48 balls left in the bag, because the balls are drawn without replacement .
[50] [13] [49] The conditional probability of winning by switching is 1/3 / 1/3 + 1/6 , which is 2 / 3 . [2] The conditional probability table below shows how 300 cases, in all of which the player initially chooses door 1, would be split up, on average, according to the location of the car and the choice of door to open by the host.
The Newton–Pepys problem is a probability problem concerning the probability of throwing sixes from a certain number of dice. [1] In 1693 Samuel Pepys and Isaac Newton corresponded over a problem posed to Pepys by a school teacher named John Smith. [2] The problem was: Which of the following three propositions has the greatest chance of success?
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Maximal lotteries are also nonmonotonic in probabilities, i.e. it is possible that the probability of an alternative decreases when a voter ranks this alternative up. [1] However, they satisfy relative monotonicity, i.e., the probability of x {\displaystyle x} relative to that of y {\displaystyle y} does not decrease when x {\displaystyle x} is ...
For the case of a single parameter and data that can be summarised in a single sufficient statistic, it can be shown that the credible interval and the confidence interval coincide if the unknown parameter is a location parameter (i.e. the forward probability function has the form (|) = ()), with a prior that is a uniform flat distribution; [6 ...