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  2. Kurtosis - Wikipedia

    en.wikipedia.org/wiki/Kurtosis

    Larger kurtosis indicates a more serious outlier problem, and may lead the researcher to choose alternative statistical methods. D'Agostino's K-squared test is a goodness-of-fit normality test based on a combination of the sample skewness and sample kurtosis, as is the Jarque–Bera test for normality.

  3. 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.

  4. Kurtosis risk - Wikipedia

    en.wikipedia.org/wiki/Kurtosis_risk

    Kurtosis risk applies to any kurtosis-related quantitative model that assumes the normal distribution for certain of its independent variables when the latter may in fact have kurtosis much greater than does the normal distribution. Kurtosis risk is commonly referred to as "fat tail" risk. The "fat tail" metaphor explicitly describes the ...

  5. 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 ...

  6. L-moment - Wikipedia

    en.wikipedia.org/wiki/L-moment

    For instance, the Laplace distribution has a kurtosis of 6 and weak exponential tails, but a larger 4th L-moment ratio than e.g. the student-t distribution with d.f.=3, which has an infinite kurtosis and much heavier tails. As an example consider a dataset with a few data points and one outlying data value.

  7. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

    If the sample has mean 0, standard deviation 1 then a line through 0 with slope 1 could be used. With more points, random deviations from a line will be less pronounced. Normal plots are often used with as few as 7 points, e.g., with plotting the effects in a saturated model from a 2-level fractional factorial experiment .

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  9. List of probability distributions - Wikipedia

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

    The Behrens–Fisher distribution, which arises in the Behrens–Fisher problem. The Cauchy distribution , an example of a distribution which does not have an expected value or a variance . In physics it is usually called a Lorentzian profile , and is associated with many processes, including resonance energy distribution, impact and natural ...