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Non-Parametric Statistics

, 2013
Beginning statistics students are usually introduced to what are called “parametric” statistics methods. Those methods utilize “models” of score distributions such as the normal (Gaussian) distribution, Poisson distribution, binomial distribution, etc.
William Ian Miller
semanticscholar   +2 more sources

Non-parametric statistics

SPSS Survival Manual, 2020
J. Pallant
semanticscholar   +2 more sources

Non-Parametric Statistics

, 1974
The theory and use of non-parametric statistics is a large subject in itself. As the name suggests, non-parametric statistics use tests whose models do not specify conditions about the parameters of the population from which the sample was drawn. Such tests are usually applied to nominal or ordinal observations (see section 1.2)—the weaker levels of ...
R. Till
semanticscholar   +2 more sources

Non-parametric statistics for nucleic acid sequence study.

Biochimie, 1985
The use of non-parametric statistics for nucleic acid sequence studies is illustrated by some examples. This method is highly flexible and allows design of specific tests for detecting sequence structure. Tests devoted to local repetitivity, codon nearest neighbors, and dinucleotide avoidance are discussed in detail.
C. Gautier, M. Gouy, S. Louail
semanticscholar   +3 more sources

NON-PARAMETRIC STATISTICS

, 2017
Xizhi Wu, Z. Geng, Qiang Zhao
semanticscholar   +2 more sources

Non-parametric tests for serial dependence in time series based on asymptotic implementations of ordinal-pattern statistics.

Chaos, 2022
Ordinal patterns can be used to construct non-parametric hypothesis tests that aim to discover (possibly non-linear) serial dependence in a real-valued time series.
C. Weiß
semanticscholar   +1 more source

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