Mann-Whitney s U Test

Rackbeta 1216 and 1218 liquid scintillation counters (LKB Wallac, Turku, Finland). Counting was continued for 5 min or until 5000 counts. Statistical significance of the differences was tested using Mann-Whitney s U test. / <0.05 was considered to be a statistically significant difference. 

The most commonly employed univariate statistical methods are analysis of variance (ANOVA) and Student s r-test [8]. These methods are parametric, that is, they require that the populations studied be approximately normally distributed. Some non-parametric methods are also popular, as, f r example, Kruskal-Wallis ANOVA and Mann-Whitney s U-test [9]. A key feature of univariate statistical methods is that data are analysed one variable at a rime (OVAT). This means that any information contained in the relation between the variables is not included in the OVAT analysis. Univariate methods are the most commonly used methods, irrespective of the nature of the data. Thus, in a recent issue of the European Journal of Pharmacology (Vol. 137), 20 out of 23 research reports used multivariate measurement. However, all of them were analysed by univariate methods. 

F-test was used for body weight, ERG parameters, hematological and blood chemistry data, and Student s t-test was used when variances between the two groups were homogeneous at p<0.05 otherwise Aspin-Welch s t-test was used. Mann-Whitney s U-test was used for differential leukocyte count. 

Fig. 7 Anti-MK aptamer and its therapeutic potential, (a) M-fold predicted secondary structures of three representative MKapt sequences, (b) SensOTgram of MKapt (49-nucleotide derivative) binding MK. MK was iimnobilized on a CM4 sensor chip and the RNA aptamers were injected for the indicated period. The was estimated to be 0.9 nM using global fitting curves (1 1 Langmuir binding) with four different RNA concentrations (0.05, 0.1, 0.2, and 0.4 mM). (c) Clinical scores for wild-type EAE mice administered phosphate buffered saline (circles) (n = 5) or 1 mg/kg (n = 5) MKapt (38-nucleotide derivative) (triangles) after EAE onset (14 days after immunization). P

Fig. 17.3 Proportion of spotted hyena pastings that were overmarks by age and sex. Males increased their overmarking activity with age (Wilcoxon signed-rank test, S = 32.5, P = 0.04), however, females did not (cub vs. subadult S = — 15.5, P = 0.24 across subadult periods N = 6, Friedman ANOVA x2 = 3.5, P = 0.17). Although male and female cubs did not differ in their frequency of overmarking (Mann-Whitney U test, U = 75, P = 0.67), a sex difference was apparent among subadults (U = 37, P = 0.02)...

The analysis of rank data, what is generally called nonparametric statistical analysis, is an exact parallel of the more traditional (and familiar) parametric methods. There are methods for the single comparison case (just as Student s t-test is used) and for the multiple comparison case (just as analysis of variance is used) with appropriate post hoc tests for exact identification of the significance with a set of groups. Four tests are presented for evaluating statistical significance in rank data the Wilcoxon Rank Sum Test, distribution-free multiple comparisons, Mann-Whitney U Test, and the Kruskall-Wallis nonparametric analysis of variance. For each of these tests, tables of distribution values for the evaluations of results can be found in any of a number of reference volumes (Gad, 1998). 

Mann-Whitneys U test (Z reported) was used to examine sex differences in carotenoid pigmentation. Means S.D. are provided for each group. 

Behavioral data may be analyzed with the Mann-Whitney U test for comparing two groups (parametric Student s t test may be used only if data are normally distributed), or analysis of variance (ANOVA) for multiple groups, followed by an appropriate post hoc test. 

The principal measure taken is the animal s latency to cross to the dark compartment at T2. This score provides an estimate of the animal s retention of the shock received at Tl. The latencies measured at T2 have a 180 second cut-off. The scores in the control group are therefore abnormally distributed because of the presence of numerous ceiling scores. It is therefore essential to apply non-parametric statistics, for example the Mann-Whitney U-test, to analyze the data. 

Thrombus score is expressed as median (minimum-maximum). Thrombus weight is given as mean SEM. For the statistical evaluation of the antithrombotic effect, the nonparametric U-Test of Mann and Whitney (thrombus score) or Student s t-test for unpaired samples (thrombus weight) is used. Significance is expressed as p < 0.05. 

Chi-.square. binomial test, runs test, one-sample Kolmogorov Smirnov test. Mann-Whitney U test. Moses test. Wald-Wolfowitz test. Kruskal Wallis te.st, Wilcoxon signed rank test. Friedman s test. Kendall s W test, Cochran s Q test... 

Statistical Analysis. Data are presented as means SEM. Statistical comparisons between groups were performed using ANOVA. Fisher s Protected Least Significant Difference (PLSD) test was used to analyze the difference in lipid levels and the Mann-Whitney U-test was used for differences in atherosclerotic levels between dietary groups. 

For experiments 1—3, in which individual males were simultaneously presented with two models in a choice test, paired, within-subjects chi-square tests were used to compare the frequency of males that clasped female-scented vs. unscented models (Exp. s 1,2) or female-scented vs. male-scented models (Exp. 3 see Snedecor Cochran, 1989). Wil-coxon signed-ranks tests were used to compare the number of clasps per male of scented vs. unscented models. In experiments 4 and 5, chi-square tests were used to compare the frequency of males that clasped models in the different treatment groups. Mann-Whitney U-tests were used to compare the number of clasps per male in the different groups. An alpha level of p <. 05, one-tailed was required for statistical significance. 

Figures 5B illustrates the relationships among the six populations studied based on their / Tm values. As the / Tm s have associated standard errors ranging from 0.15 to 0.36 C, the nodes linking the two D.laetitiae populations to the D.geniculata population are not significantly different. The other nodes are all statistically significantly different from one another even using conservative tests such as the non-parametric Mann-Whitney U-test.

Mann-Whitney U-test beer values are expected to be larger than lager values. Number of lager values greater than the individual values = 4.5 (one tie). Critical value for a one-sided test is 5, so we can just reject the null hypothesis (P = 0.05). Tukey s Quick Test coimt is 5.5, just below the critical value of 6. So tests disagree more data needed. 

For the reason, that the null hypothesis of normally distributed samples can t be rejected only by the half of the measurements, the use of parametric tests is not possible. Therefore, nonparametric tests such as Mann-Whitney U or Levene s (Hartung 1998) for the comparison of the samples shall be applied. Also the Pearson product-moment correlation assumes the norm distribution of the samples. Hence, the use of Spearman s rank correlation, which is independent on the distribution model, is more adequate. 

All statistical computations were performed using GraphPad Prism version 4.0a for Mac OS X (GraphPad Software, San Diego, California, USA). Values of experimental groups are shown as mean SEM unless otherwise stated. One-way ANOVA with Tukey s post-test analysis was used to determine statistical significance. Where appropriate, either two-tailed t-tests or Mann Whitney U tests were performed. A probability of P < 0.05 was considered to be statistically significant. 

Data are presented as mean SD. Data were tested for normal distribution. Multiple group comparison was carried out using ANOVA or Kruskal-Wallis test, with post-hoc Scheffe s test, or Mann-Whitney U test, where appropriate. Pearson or Spearman correlation coefficients were calculated, as appropriate. General linear model was employed to study the impact of independent variables on skin autofluorescence levels. P<0.05 was considered significant. Statistical program SPSS 16 was used. 

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