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  2. Coin flipping - Wikipedia

    en.wikipedia.org/wiki/Coin_flipping

    To choose two out of three, three coins are flipped, and if two coins come up the same and one different, the different one loses (is out), leaving two players. To choose one out of three, the previous is either reversed (the odd coin out is the winner ) or a regular two-way coin flip between the two remaining players can decide.

  3. Bertrand's box paradox - Wikipedia

    en.wikipedia.org/wiki/Bertrand's_box_paradox

    Bertrand's box paradox: the three equally probable outcomes after the first gold coin draw. The probability of drawing another gold coin from the same box is 0 in (a), and 1 in (b) and (c). Thus, the overall probability of drawing a gold coin in the second draw is ⁠ 0 / 3 ⁠ + ⁠ 1 / 3 ⁠ + ⁠ 1 / 3 ⁠ = ⁠ 2 / 3 ⁠.

  4. Method of conditional probabilities - Wikipedia

    en.wikipedia.org/wiki/Method_of_conditional...

    If the three coins are flipped randomly, the expected number of tails is 1.5. Thus, there must be some outcome (way of flipping the coins) so that the number of tails is at least 1.5. Since the number of tails is an integer, in such an outcome there are at least 2 tails. QED. In this example the random experiment consists of flipping three fair ...

  5. Monty Hall problem - Wikipedia

    en.wikipedia.org/wiki/Monty_Hall_problem

    The earliest of several probability puzzles related to the Monty Hall problem is Bertrand's box paradox, posed by Joseph Bertrand in 1889 in his Calcul des probabilités. [65] In this puzzle, there are three boxes: a box containing two gold coins, a box with two silver coins, and a box with one of each.

  6. Bertrand paradox (probability) - Wikipedia

    en.wikipedia.org/wiki/Bertrand_paradox_(probability)

    The Bertrand paradox is a problem within the classical interpretation of probability theory. Joseph Bertrand introduced it in his work Calcul des probabilités (1889) [1] as an example to show that the principle of indifference may not produce definite, well-defined results for probabilities if it is applied uncritically when the domain of possibilities is infinite.

  7. Gambler's fallacy - Wikipedia

    en.wikipedia.org/wiki/Gambler's_fallacy

    While a run of five heads has a probability of ⁠ 1 / 32 ⁠ = 0.03125 (a little over 3%), the misunderstanding lies in not realizing that this is the case only before the first coin is tossed. After the first four tosses in this example, the results are no longer unknown, so their probabilities are at that point equal to 1 (100%).

  8. Why do we toss coins into fountains? - AOL

    www.aol.com/why-toss-coins-fountains-160126436.html

    Where the money goes. Some well-known fountains can collect thousands of dollars in coins each year. According to an NBC report from 2016, the Trevi Fountain accumulated about $1.5 million in ...

  9. Tree diagram (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Tree_diagram_(probability...

    A tree diagram may represent a series of independent events (such as a set of coin flips) or conditional probabilities (such as drawing cards from a deck, without replacing the cards). [1] Each node on the diagram represents an event and is associated with the probability of that event.