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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. 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 ...

  4. Random assignment - Wikipedia

    en.wikipedia.org/wiki/Random_assignment

    Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment (e.g., a treatment group versus a control group) using randomization, such as by a chance procedure (e.g., flipping a coin) or a random number generator. [1]

  5. 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.

  6. 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 ...

  7. 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

  8. De Moivre–Laplace theorem - Wikipedia

    en.wikipedia.org/wiki/De_Moivre–Laplace_theorem

    The possible number of heads on each toss, k, runs from 0 to n along the horizontal axis, while the vertical axis represents the relative frequency of occurrence of the outcome k heads. The height of each dot is thus the probability of observing k heads when tossing n coins (a binomial distribution based on n trials).

  9. Mutual exclusivity - Wikipedia

    en.wikipedia.org/wiki/Mutual_exclusivity

    In the case of flipping a coin, flipping a head and flipping a tail are also mutually exclusive events. Both outcomes cannot occur for a single trial (i.e., when a coin is flipped only once). The probability of flipping a head and the probability of flipping a tail can be added to yield a probability of 1: 1/2 + 1/2 =1. [5]