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  2. Coin flipping - Wikipedia

    en.wikipedia.org/wiki/Coin_flipping

    Coin flipping, coin tossing, or heads or tails is the practice of throwing a coin in the air and checking which side is showing when it lands, in order to randomly choose between two alternatives. It is a form of sortition which inherently has two possible outcomes.

  3. Checking whether a coin is fair - Wikipedia

    en.wikipedia.org/wiki/Checking_whether_a_coin_is...

    (Note: r is the probability of obtaining heads when tossing the same coin once.) Plot of the probability density f(r | H = 7, T = 3) = 1320 r 7 (1 − r) 3 with r ranging from 0 to 1. The probability for an unbiased coin (defined for this purpose as one whose probability of coming down heads is somewhere between 45% and 55%)

  4. Gambler's fallacy - Wikipedia

    en.wikipedia.org/wiki/Gambler's_fallacy

    If a fair coin is flipped 21 times, the probability of 21 heads is 1 in 2,097,152. The probability of flipping a head after having already flipped 20 heads in a row is ⁠ 1 / 2 ⁠. Assuming a fair coin: The probability of 20 heads, then 1 tail is 0.5 20 × 0.5 = 0.5 21; The probability of 20 heads, then 1 head is 0.5 20 × 0.5 = 0.5 21

  5. St. Petersburg paradox - Wikipedia

    en.wikipedia.org/wiki/St._Petersburg_paradox

    The St. Petersburg paradox or St. Petersburg lottery [1] is a paradox involving the game of flipping a coin where the expected payoff of the lottery game is infinite but nevertheless seems to be worth only a very small amount to the participants. The St. Petersburg paradox is a situation where a naïve decision criterion that takes only the ...

  6. Penney's game - Wikipedia

    en.wikipedia.org/wiki/Penney's_game

    As this card-based version is quite similar to multiple repetitions of the original coin game, the second player's advantage is greatly amplified. The probabilities are slightly different because the odds for each flip of a coin are independent while the odds of drawing a red or black card each time is dependent on previous draws. Note that HHT ...

  7. John Edmund Kerrich - Wikipedia

    en.wikipedia.org/wiki/John_Edmund_Kerrich

    Until the advent of computer simulations, Kerrich's study, published in 1946, was widely cited as evidence of the asymptotic nature of probability. It is still regarded as a classic study in empirical mathematics. 2,000 of their fair coin flip results are given by the following table, with 1 representing heads and 0 representing tails.

  8. Fair coin - Wikipedia

    en.wikipedia.org/wiki/Fair_coin

    In probability theory and statistics, a sequence of independent Bernoulli trials with probability 1/2 of success on each trial is metaphorically called a fair coin. One for which the probability is not 1/2 is called a biased or unfair coin. In theoretical studies, the assumption that a coin is fair is often made by referring to an ideal coin.

  9. Feller's coin-tossing constants - Wikipedia

    en.wikipedia.org/wiki/Feller's_coin-tossing...

    The exact probability p(n,2) can be calculated either by using Fibonacci numbers, p(n,2) = + or by solving a direct recurrence relation leading to the same result. For higher values of k {\displaystyle k} , the constants are related to generalizations of Fibonacci numbers such as the tribonacci and tetranacci numbers.