Results 261 to 270 of about 979,711 (299)

Political rhetoric through the lens of non‐parametric statistics: are our legislators that different?

Journal of the Royal Statistical Society: Series A (Statistics in Society), 2018
We present a novel statistical analysis of legislative rhetoric in the US Senate that sheds a light on hidden patterns in the behaviour of Senators as a function of their time in office.
Iliyan R. Iliev, Xin Huang, Y. Gel
semanticscholar   +1 more source

Non-Parametric Statistical Tests

2018
Chapter 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, Fernanda Lopes, Suely R Matsubayashi   +2 more
openaire   +1 more source

Non-parametric Statistical Methods

1987
Basic statistics and econometrics courses stress methods based on assuming that the data or error term in regression models follow the normal distribution. Indeed, the efficiency of least squares estimates relies on the assumption of normality. In order to lessen the dependence of statistical inference on that assumption statisticians developed methods
openaire   +1 more source

Non-parametric statistical static timing analysis

Proceedings of the 45th annual Design Automation Conference, 2008
We present a new statistical STA framework based on Monte Carlo analysis that can deal with arbitrary statistical distribution and delay models. Order statistics (non-parametrics) is consistently adopted by which the timing analysis and criticality calculation become distribution-independent.
Masanori Imai, Takashi Sato, Noriaki Nakayama, Kazuya Masu   +3 more
openaire   +1 more source

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
openaire   +1 more source

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.
openaire   +2 more sources

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.
openaire   +1 more source

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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Genotype selection and stability analysis for seed yield of Nigella sativa using parametric and non-parametric statistics

Scientia Horticulturae, 2019
E. Shahbazi
semanticscholar   +1 more source

Non-Parametric Statistics for the Behavioral Sciences.

, 1957
Alan Stuart, S. Siegel
semanticscholar   +1 more source