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  2. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    Example distribution with positive skewness. These data are from experiments on wheat grass growth. In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The skewness value can be positive, zero, negative, or undefined.

  3. Kurtosis - Wikipedia

    en.wikipedia.org/wiki/Kurtosis

    Kurtosis calculator; Free Online Software (Calculator) computes various types of skewness and kurtosis statistics for any dataset (includes small and large sample tests).. Kurtosis on the Earliest known uses of some of the words of mathematics; Celebrating 100 years of Kurtosis a history of the topic, with different measures of kurtosis.

  4. Skew normal distribution - Wikipedia

    en.wikipedia.org/wiki/Skew_normal_distribution

    The exponentially modified normal distribution is another 3-parameter distribution that is a generalization of the normal distribution to skewed cases. The skew normal still has a normal-like tail in the direction of the skew, with a shorter tail in the other direction; that is, its density is asymptotically proportional to for some positive .

  5. Moment (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Moment_(mathematics)

    As with variance, skewness, and kurtosis, these are higher-order statistics, involving non-linear combinations of the data, and can be used for description or estimation of further shape parameters. The higher the moment, the harder it is to estimate, in the sense that larger samples are required in order to obtain estimates of similar quality.

  6. 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.

  7. L-moment - Wikipedia

    en.wikipedia.org/wiki/L-moment

    As an example consider a dataset with a few data points and one outlying data value. If the ordinary standard deviation of this data set is taken it will be highly influenced by this one point: however, if the L-scale is taken it will be far less sensitive to this data value. Consequently, L-moments are far more meaningful when dealing with ...

  8. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    A set of data that arises from the log-normal distribution has a symmetric Lorenz curve (see also Lorenz asymmetry coefficient). [ 32 ] The harmonic H {\displaystyle H} , geometric G {\displaystyle G} and arithmetic A {\displaystyle A} means of this distribution are related; [ 33 ] such relation is given by

  9. 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 ...