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  2. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    This relationship can be used to translate properties of expected values into properties of probabilities, e.g. using the law of large numbers to justify estimating probabilities by frequencies. The expected values of the powers of X are called the moments of X; the moments about the mean of X are expected values of powers of X − E[X].

  3. E-values - Wikipedia

    en.wikipedia.org/wiki/E-values

    That is: it is valid if it is an e-value. In fact, this reveals that e-values bounded to [, /] are rescaled randomized tests, that are continuously interpreted as evidence against the hypothesis. The standard e-value that takes value in [,] appears as a generalization of a level 0 test. [2]

  4. Estimating equations - Wikipedia

    en.wikipedia.org/wiki/Estimating_equations

    In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated. This can be thought of as a generalisation of many classical methods—the method of moments , least squares , and maximum likelihood —as well as some recent methods like M-estimators .

  5. Welch–Satterthwaite equation - Wikipedia

    en.wikipedia.org/wiki/Welch–Satterthwaite_equation

    In statistics and uncertainty analysis, the Welch–Satterthwaite equation is used to calculate an approximation to the effective degrees of freedom of a linear combination of independent sample variances, also known as the pooled degrees of freedom, [1] [2] corresponding to the pooled variance.

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    About 68% of values drawn from a normal distribution are within one standard deviation σ from the mean; about 95% of the values lie within two standard deviations; and about 99.7% are within three standard deviations. [8] This fact is known as the 68–95–99.7 (empirical) rule, or the 3-sigma rule.

  7. Law of total covariance - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_covariance

    Note: The conditional expected values E( X | Z) and E( Y | Z) are random variables whose values depend on the value of Z. Note that the conditional expected value of X given the event Z = z is a function of z. If we write E( X | Z = z) = g(z) then the random variable E( X | Z) is g(Z). Similar comments apply to the conditional covariance.

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  9. e (mathematical constant) - Wikipedia

    en.wikipedia.org/wiki/E_(mathematical_constant)

    The number e is a mathematical constant approximately equal to 2.71828 that is the base of the natural logarithm and exponential function.It is sometimes called Euler's number, after the Swiss mathematician Leonhard Euler, though this can invite confusion with Euler numbers, or with Euler's constant, a different constant typically denoted .