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  2. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    The variance of a probability distribution is analogous to the moment of inertia in classical mechanics of a corresponding mass distribution along a line, with respect to rotation about its center of mass. [citation needed] It is because of this analogy that such things as the variance are called moments of probability distributions.

  3. Law of total variance - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_variance

    Law of total variance. In probability theory, the law of total variance[1] or variance decomposition formula or conditional variance formulas or law of iterated variances also known as Eve's law, [2] states that if and are random variables on the same probability space, and the variance of is finite, then. In language perhaps better known to ...

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    t. e. In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [1][2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [3]

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is f ( x ) = 1 2 π σ 2 e − ( x − μ ) 2 2 σ 2 . {\displaystyle f(x)={\frac {1}{\sqrt {2\pi \sigma ^{2}}}}e^{-{\frac ...

  6. Continuous uniform distribution - Wikipedia

    en.wikipedia.org/.../Continuous_uniform_distribution

    Continuous uniform. In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. [1]

  7. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    Then, the distribution of the random variable. is called the log-normal distribution with parameters and . These are the expected value (or mean) and standard deviation of the variable's natural logarithm, not the expectation and standard deviation of itself. Relation between normal and log-normal distribution.

  8. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    In probability and statistics, Student's t distribution (or simply the t distribution) is a continuous probability distribution that generalizes the standard normal distribution. Like the latter, it is symmetric around zero and bell-shaped. However, has heavier tails and the amount of probability mass in the tails is controlled by the parameter ...

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

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

    A product distribution is a probability distribution constructed as the distribution of the product of random variables having two other known distributions. Given two statistically independent random variables X and Y, the distribution of the random variable Z that is formed as the product is a product distribution.

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