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  2. Parametric statistics - Wikipedia

    en.wikipedia.org/wiki/Parametric_statistics

    Parametric statistical methods are used to compute the 2.33 value above, given 99 independent observations from the same normal distribution. A non-parametric estimate of the same thing is the maximum of the first 99 scores. We don't need to assume anything about the distribution of test scores to reason that before we gave the test it was ...

  3. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Parametric tests assume that the data follow a particular distribution, typically a normal distribution, while non-parametric tests make no assumptions about the distribution. [7] Non-parametric tests have the advantage of being more resistant to misbehaviour of the data, such as outliers . [ 7 ]

  4. Nonparametric statistics - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_statistics

    Hypothesis (d) is also non-parametric but, in addition, it does not even specify the underlying form of the distribution and may now be reasonably termed distribution-free. Notwithstanding these distinctions, the statistical literature now commonly applies the label "non-parametric" to test procedures that we have just termed "distribution-free ...

  5. Surrogate data testing - Wikipedia

    en.wikipedia.org/wiki/Surrogate_data_testing

    The last surrogate data methods do not depend on a particular model, nor on any parameters, thus they are non-parametric methods. These surrogate data methods are usually based on preserving the linear structure of the original series (for instance, by preserving the autocorrelation function , or equivalently the periodogram , an estimate of ...

  6. Category:Nonparametric statistics - Wikipedia

    en.wikipedia.org/wiki/Category:Nonparametric...

    Nonparametric statistics is a branch of statistics concerned with non-parametric statistical models and non-parametric statistical tests. Non-parametric statistics are statistics that do not estimate population parameters. In contrast, see parametric statistics. Nonparametric models differ from parametric models in that the model structure is ...

  7. Parameter identification problem - Wikipedia

    en.wikipedia.org/wiki/Parameter_identification...

    It is closely related to non-identifiability in statistics and econometrics, which occurs when a statistical model has more than one set of parameters that generate the same distribution of observations, meaning that multiple parameterizations are observationally equivalent.

  8. New Orleans attacker did not act alone, FBI believes - AOL

    www.aol.com/news/scene-just-horrific-witnesses...

    The suspect in the New Orleans attack that killed 10 people on New Year's Day did not act alone, US investigators believe. Shamsud-Din Jabbar, a 42-year-old US citizen, is believed to have driven ...

  9. Parametric model - Wikipedia

    en.wikipedia.org/wiki/Parametric_model

    Parametric models are contrasted with the semi-parametric, semi-nonparametric, and non-parametric models, all of which consist of an infinite set of "parameters" for description. The distinction between these four classes is as follows: [citation needed] in a "parametric" model all the parameters are in finite-dimensional parameter spaces;