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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. 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 ...

  4. 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.

  5. Multimodal distribution - Wikipedia

    en.wikipedia.org/wiki/Multimodal_distribution

    The kurtosis is here defined to be the standardised fourth moment around the mean. The value of b lies between 0 and 1. [26] The logic behind this coefficient is that a bimodal distribution with light tails will have very low kurtosis, an asymmetric character, or both – all of which increase this coefficient. The formula for a finite sample ...

  6. Matching (statistics) - Wikipedia

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

    Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).

  7. Hypergeometric distribution - Wikipedia

    en.wikipedia.org/wiki/Hypergeometric_distribution

    In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws, without replacement, from a finite population of size that contains exactly objects with that feature, wherein each draw is either a success or a failure.

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    www.aol.com/her-daughters-suicide-shocked...

    This mom lost her 15-year-old daughter to suicide. She wants people to know that suicide and depression aren't linear.

  9. Talk:Kurtosis - Wikipedia

    en.wikipedia.org/wiki/Talk:Kurtosis

    The expected Kurtosis for sample of IID standard normal data is 3 (see the wiki article on the normal distribution for more). We tend to refer to excess kurtosis as the sample kurtosis of a series -3 for that reason.. —Preceding unsigned comment added by 62.30.156.106 21:42, 14 March 2008 (UTC)