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  2. Conditional variance - Wikipedia

    en.wikipedia.org/wiki/Conditional_variance

    In words: the variance of Y is the sum of the expected conditional variance of Y given X and the variance of the conditional expectation of Y given X. The first term captures the variation left after "using X to predict Y", while the second term captures the variation due to the mean of the prediction of Y due to the randomness of X.

  3. Conditional expectation - Wikipedia

    en.wikipedia.org/wiki/Conditional_expectation

    In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated with respect to the conditional probability distribution. If the random variable can take on only a finite number of values, the "conditions" are that the variable can only take on a subset of ...

  4. Law of total variance - Wikipedia

    en.wikipedia.org/wiki/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

  5. Variance function - Wikipedia

    en.wikipedia.org/wiki/Variance_function

    To calculate the variance function ... The smoothed conditional variance against the smoothed conditional mean. The quadratic shape is indicative of the Gamma ...

  6. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    Conditional expectation; Expectation (epistemic) Expectile – related to expectations in a way analogous to that in which quantiles are related to medians; Law of total expectation – the expected value of the conditional expected value of X given Y is the same as the expected value of X; Median – indicated by in a drawing above

  7. Law of total covariance - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_covariance

    The nomenclature in this article's title parallels the phrase law of total variance. Some writers on probability call this the "conditional covariance formula" [2] or use other names. Note: The conditional expected values E( X | Z) and E( Y | Z) are random variables whose values depend on the value of Z.

  8. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    This estimate is sometimes referred to as the "geometric CV" (GCV), [19] [20] due to its use of the geometric variance. Contrary to the arithmetic standard deviation, the arithmetic coefficient of variation is independent of the arithmetic mean. The parameters μ and σ can be obtained, if the arithmetic mean and the arithmetic variance are known:

  9. Condition number - Wikipedia

    en.wikipedia.org/wiki/Condition_number

    Condition numbers can also be defined for nonlinear functions, and can be computed using calculus.The condition number varies with the point; in some cases one can use the maximum (or supremum) condition number over the domain of the function or domain of the question as an overall condition number, while in other cases the condition number at a particular point is of more interest.