Non-Parametric Statistic
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A Non-Parametric Statistic is a statistic that is a non-parametric function/non-parametric model.
- Example(s):
- Counter-Example(s):
- a Parametric Statistic, such as a Wald statistic.
- See: Nonparametric Statistics, Probability Distribution, Statistics, Parametrization, Descriptive Statistics, Statistical Inference.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Nonparametric_statistics Retrieved:2015-11-22.
- 'Nonparametric statistics are statistics not based on parameterized families of probability distributions. They include both descriptive and inferential statistics. The typical parameters are the mean, variance, etc. Unlike parametric statistics, nonparametric statistics make no assumptions about the probability distributions of the variables being assessed. The difference between parametric models and non-parametric models is that the former has a fixed number of parameters, while the latter grows the number of parameters with the amount of training data. Note that the non-parametric model is not none-parametric: parameters are determined by the training data, not the model.
2017
- (Investopedia, 2017) ⇒ https://www.investopedia.com/terms/n/nonparametric-statistics.asp Retrieved: 2017-12-03.
- Nonparametric statistics refer to a statistical method wherein the data is not required to fit a normal distribution. Nonparametric statistics uses data that is often ordinal, meaning it does not rely on numbers, but rather a ranking or order of sorts. For example, a survey conveying consumer preferences ranging from like to dislike would be considered ordinal data.
Nonparametric statistics have gained appreciation due to their ease of use. As the need for parameters is relieved, the data becomes more applicable to a larger variety of tests. This type of statistics can be used without the mean, sample size, standard deviation, or the estimation of any other related parameters when none of that information is available.
- Nonparametric statistics refer to a statistical method wherein the data is not required to fit a normal distribution. Nonparametric statistics uses data that is often ordinal, meaning it does not rely on numbers, but rather a ranking or order of sorts. For example, a survey conveying consumer preferences ranging from like to dislike would be considered ordinal data.