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  2. Random variable - Wikipedia

    en.wikipedia.org/wiki/Random_variable

    A mixed random variable is a random variable whose cumulative distribution function is neither discrete nor everywhere-continuous. [10] It can be realized as a mixture of a discrete random variable and a continuous random variable; in which case the CDF will be the weighted average of the CDFs of the component variables. [10]

  3. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    Furthermore, it covers distributions that are neither discrete nor continuous nor mixtures of the two. An example of such distributions could be a mix of discrete and continuous distributions—for example, a random variable that is 0 with probability 1/2, and takes a random value from a normal distribution with probability 1/2.

  4. Talk:Random variable - Wikipedia

    en.wikipedia.org/wiki/Talk:Random_variable

    It is not true that for every non-discrete random variable, the probability of a specific value is zero. Later in the same paragraph such "mixed" variables which are neither discrete nor continuous are mentioned, which contradicts the statement that there are only discrete and continuous variables. Tomek81 20:04, 21 November 2010 (UTC)

  5. Random graph - Wikipedia

    en.wikipedia.org/wiki/Random_graph

    In mathematics, random graph is the general term to refer to probability distributions over graphs. Random graphs may be described simply by a probability distribution, or by a random process which generates them. [1] [2] The theory of random graphs lies at the intersection between graph theory and probability theory.

  6. Binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Binomial_distribution

    In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own Boolean-valued outcome: success (with probability p) or failure (with probability q = 1 − p).

  7. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    The second row is the same generator with a seed of 3, which produces a cycle of length 2. Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation.

  8. Indonesia says Apple's $100 million investment proposal ...

    www.aol.com/news/indonesia-says-apples-100...

    Indonesia said a $100 million investment proposal from Apple to build an accessory and component plant was not enough for the country to allow the tech giant to sell its latest iPhone model, its ...

  9. Singular distribution - Wikipedia

    en.wikipedia.org/wiki/Singular_distribution

    On the other hand, neither does it have a probability density function, since the Lebesgue integral of any such function would be zero. In general, distributions can be described as a discrete distribution (with a probability mass function), an absolutely continuous distribution (with a probability density), a singular distribution (with ...