Hi I'm trying to use a Mann-Whitney test in a PCR data, like this: # Case the samples are similar: x1 <- c(19.0370805,17.51822,18.524912) y1 <- c(20.541484,22.039175,20.542968) w1 <- wilcox.test(x1,y1, paired = FALSE, alternative = c("two.sided")) Wilcoxon rank sum test data: m and f W = 0, p-value = 0.1 alternative hypothesis: true location shift is not equal to 0 # Case the samples are not similar: x2 <- c(3.9934205, 3.499646, 4.489782) y2 <- c(20.541484,22.039175,20.542968) w2 <- wilcox.test(m,f, paired = FALSE, alternative = c("two.sided")) Wilcoxon rank sum test data: m and f W = 0, p-value = 0.1 alternative hypothesis: true location shift is not equal to 0 I obtain the same result: pvalue > 0.05, so i don't reject the null hypothesis, that both samples came from the same distribution. If i test other numbers the result is the same always. Thanks.

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The Wilcoxon test is a permutation test. We don't actually do the permutations, because the p-values are tabulated. However, because it is a permutation test, the smallest possible p-value is 1/#permutations. So for tiny sample sizes (e.g. 3) you cannot get significant results. --Naomi At 12:21 PM 12/11/2007, Patricia Garcia wrote: >Hi >I'm trying to use a Mann-Whitney test in a PCR data, like this: > > ># Case the samples are similar: >x1 <- c(19.0370805,17.51822,18.524912) >y1 <- c(20.541484,22.039175,20.542968) >w1 <- wilcox.test(x1,y1, paired = FALSE, alternative = c("two.sided")) > > > Wilcoxon rank sum test > > data: m and f > W = 0, p-value = 0.1 > alternative hypothesis: true location shift is not equal to 0 > ># Case the samples are not similar: >x2 <- c(3.9934205, 3.499646, 4.489782) >y2 <- c(20.541484,22.039175,20.542968) >w2 <- wilcox.test(m,f, paired = FALSE, alternative = c("two.sided")) > > > Wilcoxon rank sum test > > data: m and f > W = 0, p-value = 0.1 > alternative hypothesis: true location shift is not equal to 0 > > > >I obtain the same result: pvalue > 0.05, so i don't reject the null >hypothesis, that both samples came from the same distribution. >If i test other numbers the result is the same always. >Thanks. > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor >Search the archives: >http://news.gmane.org/gmane.science.biology.informatics.conductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111

Hi Patricia, i believe the result is the same for your two examples because the ranks are the same (this test only sees how the values rank) for 2 sets of size 3, you can never get a p-value lower than the one you get for your two examples simply because that configuration (all values in one are higher than those in the other) is the least likely to occur. you might want to try other tests Caroline On Dec 11, 2007 6:21 PM, Patricia Garcia <patricia.garcia.gonzalez at="" gmail.com=""> wrote: > Hi > I'm trying to use a Mann-Whitney test in a PCR data, like this: > > > # Case the samples are similar: > x1 <- c(19.0370805,17.51822,18.524912) > y1 <- c(20.541484,22.039175,20.542968) > w1 <- wilcox.test(x1,y1, paired = FALSE, alternative = c("two.sided")) > > > Wilcoxon rank sum test > > data: m and f > W = 0, p-value = 0.1 > alternative hypothesis: true location shift is not equal to 0 > > # Case the samples are not similar: > x2 <- c(3.9934205, 3.499646, 4.489782) > y2 <- c(20.541484,22.039175,20.542968) > w2 <- wilcox.test(m,f, paired = FALSE, alternative = c("two.sided")) > > > Wilcoxon rank sum test > > data: m and f > W = 0, p-value = 0.1 > alternative hypothesis: true location shift is not equal to 0 > > > > I obtain the same result: pvalue > 0.05, so i don't reject the null > hypothesis, that both samples came from the same distribution. > If i test other numbers the result is the same always. > Thanks. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >