1952
DOI: 10.1080/01621459.1952.10483441
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Use of Ranks in One-Criterion Variance Analysis

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Cited by 9,173 publications
(4,724 citation statements)
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“…Repeating this procedure, sampling different numbers of SNPs (i.e. 50, 100, 200, 400, 800, 1600, 3200, 6400), the accuracy for classification was tested using a Kruskal-Wallis rank sum test (Kruskal and Wallis, 1952), to evaluate if any increment in accuracy was significant. These results are shown in Table 1.…”
Section: Resultsmentioning
confidence: 99%
“…Repeating this procedure, sampling different numbers of SNPs (i.e. 50, 100, 200, 400, 800, 1600, 3200, 6400), the accuracy for classification was tested using a Kruskal-Wallis rank sum test (Kruskal and Wallis, 1952), to evaluate if any increment in accuracy was significant. These results are shown in Table 1.…”
Section: Resultsmentioning
confidence: 99%
“…Mycorrhizal parameters, biometrical data and phosphorus content values were analyzed using the nonparametric Kruskal-Wallis test (Kruskal 1952;Kruskal and Wallis 1952). The statistical significance was assessed at the 95 % level.…”
Section: Resultsmentioning
confidence: 99%
“…Since most variables did not comply with normal Gaussian distribution as determined by the Kolmogorov-Smirnov test, 18,19 a nonparametric Mann-Whitney U-test 20 or Kruskal-Wallis test 21 was applied in order to compare independent samples of continuous variables. All p-values were based on 2-sided tests and the threshold to accept statistical significance was set at the alpha level 0.05.…”
Section: Resultsmentioning
confidence: 99%