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Non-Parametric Statistical Tests
2018Chapter 10 introduces the most commonly used non-parametric tests, as well as the appropriate situations for their use. It also examines concepts of sample size, power, and validity when using these tests. In addition, this chapter discusses the major advantages and disadvantages of non-parametric tests, and how they compare to their optimal parametric
Felipe Fregni +2 more
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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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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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A comparison of parametric and non-parametric statistical tests
BMJ, 2015Researchers investigated the effectiveness of corticosteroids in reducing respiratory disorders in infants born at 34-36 weeks’ gestation. A randomised placebo controlled trial was performed. The intervention was treatment with betamethasone, 12 mg intramuscularly daily for two consecutive days at 34-36 weeks of pregnancy.
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Some Further Non-parametric Statistics
1971So 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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Statistical Analysis V: Non-parametric Statistics
1987The 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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Sampling and non-parametric statistics
Revista Mexicana de Oftalmología (English Edition), 2023Christian Fau, Emmanuel Vazquez-Ortiz
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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.openaire +1 more source
Practical Non-Parametric Statistics.
Biometrics, 1981B. M. Brown, W. J. Conover
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