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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 ...
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An introduction to non-parametric statistics

Analytical Methods, 2013
Non-parametric statistical methods, which make fewer assumptions about population error distributions, have perhaps been unjustly neglected in the analytical sciences. A major advantage is that some of them are so simple that they can be used "at the bench."
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Some Further Non-parametric Statistics

1971
So far we have not drawn the reader ’s attention to the distinction between the so-called parametric and the so- called non-parametric methods used in inference statistics. Although we have not done this, we have in fact already described various statistical procedures of both kinds.
T. G. Connolly, W. Sluckin
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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
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Statistical tests (part 3): non-parametric tests

Nursing Standard, 1993
The previous two articles in this series (1,2) have considered in some detail the descriptive and parametric approaches to statistical analysis. This final article now considers principally the non-parametric approach to statistical analysis and, briefly, looks at the concepts of dimension reduction, factor analysis and confidence limits.
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Statistical Analysis V: Non-parametric Statistics

1987
The NPAR procedure allows the user to carry out a variety of non-parametric statistical tests. Unlike parametric statistics (including the t-test, anova, the product-moment correlation, etc.) non-parametric statistics make few assumptions about the nature of the data.
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Parametric v non-parametric statistical tests

BMJ, 2012
Researchers investigated five year mortality in patients with chronic heart failure by comparing those with impaired left ventricular function (n=359) with those with preserved function (n=163).1 A prospective cohort study design was used, with patients enrolled if they had had stable symptomatic chronic heart failure for at least three months ...
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Non-Parametric Statistic Methods

 In this chapter, we will explore various methods and statistical tests used in hypothesis validation and sample comparison. We will begin with an introduction to the formulation of scientific and statistical hypotheses and discuss the determination of the appropriate sample size.
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

Topics in non-parametric Bayesian statistics

2003
Abstract The intersection set of Bayesian and non-parametric statistics was almost empty until about 1973, but now seems to be growing at a healthy rate. This article gives an overview of various theoretical and applied research themes in this field, partly complementing and extending recent reviews of Dey et al. (1998) and Walker et al.
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