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  2. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    In probability theory and statistics, skewness is a measure ... graph, the values on the right side of the distribution taper differently from the values on the left ...

  3. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    When the smaller values tend to be farther away from the mean than the larger values, one has a skew distribution to the left (i.e. there is negative skewness), one may for example select the square-normal distribution (i.e. the normal distribution applied to the square of the data values), [1] the inverted (mirrored) Gumbel distribution, [1 ...

  4. Shape of a probability distribution - Wikipedia

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

    Considerations of the shape of a distribution arise in statistical data analysis, where simple quantitative descriptive statistics and plotting techniques such as histograms can lead on to the selection of a particular family of distributions for modelling purposes. The normal distribution, often called the "bell curve" Exponential distribution

  5. List of probability distributions - Wikipedia

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

    It is ubiquitous in nature and statistics due to the central limit theorem: every variable that can be modelled as a sum of many small independent, identically distributed variables with finite mean and variance is approximately normal. The normal-exponential-gamma distribution; The normal-inverse Gaussian distribution

  6. Hyperbolic secant distribution - Wikipedia

    en.wikipedia.org/wiki/Hyperbolic_secant_distribution

    In it, is a measure of left skew and a measure of right skew, in case the parameters are both positive. They have to be both positive or negative, with a = b {\displaystyle a=b} being the hyperbolic secant - and therefore symmetric - and h ( x ) r {\displaystyle h(x)^{r}} being its further reshaped form.

  7. Heavy-tailed distribution - Wikipedia

    en.wikipedia.org/wiki/Heavy-tailed_distribution

    The distribution of a random variable X with distribution function F is said to have a long right tail [1] if for all t > 0, [> + >] =,or equivalently ¯ (+) ¯ (). This has the intuitive interpretation for a right-tailed long-tailed distributed quantity that if the long-tailed quantity exceeds some high level, the probability approaches 1 that it will exceed any other higher level.

  8. Skew partition - Wikipedia

    en.wikipedia.org/wiki/Skew_partition

    In graph theory, a skew partition of a graph is a partition of its vertices into two subsets, such that the induced subgraph formed by one of the two subsets is disconnected and the induced subgraph formed by the other subset is the complement of a disconnected graph. Skew partitions play an important role in the theory of perfect graphs.

  9. 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.