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  2. Algebra of random variables - Wikipedia

    en.wikipedia.org/wiki/Algebra_of_random_variables

    An expectation E on an algebra A of random variables is a normalized, positive linear functional. What this means is that E[k] = k where k is a constant; E[X * X] ≥ 0 for all random variables X; E[X + Y] = E[X] + E[Y] for all random variables X and Y; and; E[kX] = kE[X] if k is a constant. One may generalize this setup, allowing the algebra ...

  3. Wald's equation - Wikipedia

    en.wikipedia.org/wiki/Wald's_equation

    . the random variables (X n) n∈ all have the same distribution. Note that the random variables of the sequence (X n) n∈ don't need to be independent. The interesting point is to admit some dependence between the random number N of terms and the sequence (X n) n∈.

  4. Random variable - Wikipedia

    en.wikipedia.org/wiki/Random_variable

    A random variable (also called random quantity, aleatory variable, or stochastic variable) is a mathematical formalization of a quantity or object which depends on random events. [1] The term 'random variable' in its mathematical definition refers to neither randomness nor variability [ 2 ] but instead is a mathematical function in which

  5. Category:Algebra of random variables - Wikipedia

    en.wikipedia.org/wiki/Category:Algebra_of_random...

    Download as PDF; Printable version; ... Pages in category "Algebra of random variables" ... Distribution of the product of two random variables;

  6. Distribution of the product of two random variables - Wikipedia

    en.wikipedia.org/wiki/Distribution_of_the...

    A more general case of this concerns the distribution of the product of a random variable having a beta distribution with a random variable having a gamma distribution: for some cases where the parameters of the two component distributions are related in a certain way, the result is again a gamma distribution but with a changed shape parameter ...

  7. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Thus the discrete random variables (i.e. random variables whose probability distribution is discrete) are exactly those with a probability mass function = (=). In the case where the range of values is countably infinite, these values have to decline to zero fast enough for the probabilities to add up to 1.

  8. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    This does not look random, but it satisfies the definition of random variable. This is useful because it puts deterministic variables and random variables in the same formalism. The discrete uniform distribution, where all elements of a finite set are equally likely. This is the theoretical distribution model for a balanced coin, an unbiased ...

  9. Free probability - Wikipedia

    en.wikipedia.org/wiki/Free_probability

    Later connections to random matrix theory, combinatorics, representations of symmetric groups, large deviations, quantum information theory and other theories were established. Free probability is currently undergoing active research. Typically the random variables lie in a unital algebra A such as a C*-algebra or a von Neumann algebra.

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