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  2. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    The skewness value can be positive, zero, negative, or undefined. For a unimodal distribution (a distribution with a single peak), negative skew commonly indicates that the tail is on the left side of the distribution, and positive skew indicates that the tail is on the right. In cases where one tail is long but the other tail is fat, skewness ...

  3. Shape of a probability distribution - Wikipedia

    en.wikipedia.org/wiki/Shape_of_a_probability...

    In statistics, the concept of the shape of a probability distribution arises in questions of finding an appropriate distribution to use to model the statistical properties of a population, given a sample from that population.

  4. Coskewness - Wikipedia

    en.wikipedia.org/wiki/Coskewness

    where S X is the skewness of X and is the standard deviation of X. It follows that the sum of two random variables can be skewed (S X+Y ≠ 0) even if both random variables have zero skew in isolation (S X = 0 and S Y = 0). The standardized rank coskewness RS(X, Y, Z) satisfies the following properties: [4]

  5. Shape parameter - Wikipedia

    en.wikipedia.org/wiki/Shape_parameter

    Most simply, they can be estimated in terms of the higher moments, using the method of moments, as in the skewness (3rd moment) or kurtosis (4th moment), if the higher moments are defined and finite. Estimators of shape often involve higher-order statistics (non-linear functions of the data), as in the higher moments, but linear estimators also ...

  6. Method of moments (statistics) - Wikipedia

    en.wikipedia.org/wiki/Method_of_moments_(statistics)

    In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.

  7. Skewed generalized t distribution - Wikipedia

    en.wikipedia.org/wiki/Skewed_generalized_t...

    where is the beta function, is the location parameter, > is the scale parameter, < < is the skewness parameter, and > and > are the parameters that control the kurtosis. and are not parameters, but functions of the other parameters that are used here to scale or shift the distribution appropriately to match the various parameterizations of this distribution.

  8. Fat-tailed distribution - Wikipedia

    en.wikipedia.org/wiki/Fat-tailed_distribution

    A fat-tailed distribution is a probability distribution that exhibits a large skewness or kurtosis, relative to that of either a normal distribution or an exponential distribution. [when defined as?] In common usage, the terms fat-tailed and heavy-tailed are sometimes synonymous; fat-tailed is sometimes also defined as a subset of heavy-tailed ...

  9. Data transformation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    Meaning: A k-fold increase in X is associated with an average of ⁡ units increase in Y. For illustrative purposes, if base-10 logarithm were used instead of natural logarithm in the above transformation and the same symbols ( a and b ) are used to denote the regression coefficients, then a tenfold increase in X would result in an average ...