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  2. 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%)

  3. Fair coin - Wikipedia

    en.wikipedia.org/wiki/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 . John Edmund Kerrich performed experiments in coin flipping and found that a coin made from a wooden disk about the size of a crown and coated on one side with lead ...

  4. Martingale (probability theory) - Wikipedia

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

    A gambler's fortune (capital) is a martingale if all the betting games which the gambler plays are fair. The gambler is playing a game of coin flipping. Suppose X n is the gambler's fortune after n tosses of a fair coin, such that the gambler wins $1 if the coin toss outcome is heads and loses $1 if the coin toss outcome is tails. The gambler's ...

  5. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    Consider a simple statistical model of a coin flip: a single parameter that expresses the "fairness" of the coin. The parameter is the probability that a coin lands heads up ("H") when tossed. can take on any value within the range 0.0 to 1.0. For a perfectly fair coin, =. Imagine flipping a fair coin twice, and observing two heads in two ...

  6. Martingale (betting system) - Wikipedia

    en.wikipedia.org/wiki/Martingale_(betting_system)

    In this example, the probability of losing the entire bankroll and being unable to continue the martingale is equal to the probability of 6 consecutive losses: (10/19) 6 = 2.1256%. The probability of winning is equal to 1 minus the probability of losing 6 times: 1 − (10/19) 6 = 97.8744%. The expected amount won is (1 × 0.978744) = 0.978744.

  7. Random walk - Wikipedia

    en.wikipedia.org/wiki/Random_walk

    An elementary example of a random walk is the random walk on the integer number line, , which starts at 0 and at each step moves +1 or −1 with equal probability. This walk can be illustrated as follows. A marker is placed at zero on the number line, and a fair coin is flipped.

  8. Coin flipping - Wikipedia

    en.wikipedia.org/wiki/Coin_flipping

    Tossing a coin. 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. The party who calls the side that is facing up when the coin ...

  9. Bernoulli process - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_process

    A Bernoulli process is a finite or infinite sequence of independent random variables X 1, X 2, X 3, ..., such that . for each i, the value of X i is either 0 or 1;; for all values of , the probability p that X i = 1 is the same.