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Statistical Tests Based on Empty Cells

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Domański C., Uniwersytet Łódzki; Wydział Ekonomiczno-Socjologiczny; Instytut Statystyki i Demografii
Acta Universitatis Lodziensis. Folia Oeconomica
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2012
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vol. 269
EN
In professional literature on statistics, a constantly growing interest is observed in non-parametric methods. Commonly these methods are based on counting, rank or position statistics and on a number or length of series. In this paper, the least popular tests, namely tests based on a number of empty cells, are presented. David-Hellwig test and a two-sample consistency test are considered. Empirical power of the tests is presented in comparison to classic tests: Kolmogorov and Shapio-Wilk test for testing normality of a distribution and t-Student’s and Wilcoxon tests for testing consistency of two distributions.
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Some Remarks on Empirical Power of Tests for Pairs

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Domański C., University of Łódź C. o. S. M.
Acta Universitatis Lodziensis. Folia Oeconomica
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2006
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vol. 196
EN
The paper deals with the tests for paired variables called also tests for pairs of variables. The observations are made of pairs of measurements. They can be correlated. It causes the necessity of applying another significance test of differences for example between means than in case of independent samples. We compare the power of nonparametric tests: sign test, Munzel and Wilcoxon tests with the Student’s test for pairs.
PL
W artykule prezentowane są testy dla zmiennych połączonych, zwanych także testami dla par zmiennych. Obserwacje składają się z par pomiarów. Mogą być one skorelowane. Sytuacja ta sprawia, że należy zastosować inny test istotności różnic, np. pomiędzy średnimi aniżeli w przypadku prób niezależnych. Porównujemy moc testów nieparametrycznych: znaków, Wilcoxona i Munzela z testem t-Studenta dla par.
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