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  2. Alias method - Wikipedia

    en.wikipedia.org/wiki/Alias_method

    Internally, the algorithm consults two tables, a probability table U i and an alias table K i (for 1 ≤ i ≤ n). To generate a random outcome, a fair die is rolled to determine an index i into the two tables. A biased coin is then flipped, choosing a result of i with probability U i, or K i otherwise (probability 1 − U i). [4]

  3. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    Roll a die 10 times and save the results into variables , …,. Independent : Each outcome of the die roll will not affect the next one, which means the 10 variables are independent from each other. Identically distributed : Regardless of whether the die is fair or weighted, each roll will have the same probability of seeing each result as ...

  4. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    Consider the flip of two fair coins; let and be discrete random variables associated with the outcomes of the first and second coin flips respectively. Each coin flip is a Bernoulli trial and has a Bernoulli distribution. If a coin displays "heads" then the associated random variable takes the value 1, and it takes the value 0 otherwise.

  5. Checking whether a coin is fair - Wikipedia

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

    It is based on the coin flip used widely in sports and other situations where it is required to give two parties the same chance of winning. Either a specially designed chip or more usually a simple currency coin is used, although the latter might be slightly "unfair" due to an asymmetrical weight distribution, which might cause one state to ...

  6. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    For example, if two fair six-sided dice are thrown to generate two uniformly distributed integers, and , each in the range from 1 to 6, inclusive, the 36 possible ordered pairs of outcomes (,) constitute a sample space of equally likely events. In this case, the above formula applies, such as calculating the probability of a particular sum of ...

  7. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    Entropy Η(X) (i.e. the expected surprisal) of a coin flip, measured in bits, graphed versus the bias of the coin Pr(X = 1), where X = 1 represents a result of heads. [ 10 ] : 14–15 Here, the entropy is at most 1 bit, and to communicate the outcome of a coin flip (2 possible values) will require an average of at most 1 bit (exactly 1 bit for ...

  8. Fair coin - Wikipedia

    en.wikipedia.org/wiki/Fair_coin

    A fair coin, when tossed, should have an equal chance of landing either side up. 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.

  9. Dice notation - Wikipedia

    en.wikipedia.org/wiki/Dice_notation

    These include whether a specially marked die (called the Mayhem die) has rolled highest, the lowest number rolled, and whether any two dice show the same number. One other commonly used variant of the 6-sided dice roll is the d3, which is a 6-sided die roll, with the result divided by 2. The average result is 2, and the standard deviation is 0.816.