similar to: Mann-Whitney U test discrepancies

Hi, Could someone please tell me how to perform a Mann-Whitney U test on a dataset with 2 groups where one group has more data values than another? I have split up my 2 groups into 2 columns in my .txt file i'm using with R. Here is the code i have so far... group1 <- c(LeafArea2) group2 <- c(LeafArea1) wilcox.test(group1, group2) This code works for datasets with the same number

Dear r-helpers, I want to test groups of samples for significant differences. Question: Does Group1 differ significantly from group2. This is a question to be answered by mann-whitney-u-test. I know that I can use wilcox.test with 2 samples. My problem: How can r perform the test automatically if there are more than 2 groups in my data frame. Test group1 vs. 2, 1 vs. 3, 1 vs. 4, etc. This is

Hi all, The Kruskal-Wallis test is a generalization of the two-sample Mann-Whitney test to *k* samples. That being the case, the Kruskal-Wallis test with *k*=2 should give an identical p-value to the Mann-Whitney test, should it not? x1<-c(1:5) x2<-c(6,8,9,11) a<-wilcox.test(x1,x2,paired=FALSE) b<-kruskal.test(list(x1,x2),paired=FALSE) a$p.value [1] 0.01587302 b$p.value [1]

Dear Sir, I am comparing two samples using wilcox.test in R. Literature appears to describe mann whitney u test as the most appropriate test to use on my data. is the wilcox.test function equivalent to mann-whitney u? Is there a way to gain the U-value as apposed to the W-value in R? Thank you

Given this example #start code a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) wilcox.test(a, b, paired=FALSE) #sum of rank for first sample sum.rank.a <-

Hi, I know that I can perform a Mann-Whitney U test with wilcox.test(x,y) But instead of an U-value I get a W-Value. Is it possible to change this?

Hi, I have a statistical question. To apply the Mann Whitney test to compare a pair of vectors, they must to have the same length ? Thanks, Rodrigo [[alternative HTML version deleted]]

Hello, I'm having some issues grouping cases for some Mann-Whitney U tests I'm attempting to run. I'm willing to use wilcox.test if it'll work; I've also tried wilcox_test() from the "coin" package. Here's the deal: for each column (A through H), I would like to run the two-sample independent test, comparing Group 5 (CD8.14 through CD8.17) to Group 6 (CD8.18

Does anyone have a piece of code or know how I can use R to generate a table of critical values for the Mann-Whitney (aka Wilcoxon Rank Sum) test. Ideally, I'd like a table that contains the critical values for any two samples of size 3 through 30. I could use Monte Carlo simulation or the normal approximation when n1 and n2 are greater than, 10, but I figured someone may know how to

An earlier post had posed the question: "Does anybody know what is relation between 'T' value calculated by 'wilcox_test' function (coin package) and more common 'W' value?" I found the question interesting and ran the commands in R and SPSS. The W reported by R did not seem to correspond to either Mann-Whitney U, Wilcoxon W or the Z which I have more

>Hola colegas, no encuentro como hacer el Mann-Whitney U Test en R. > > Alguna solución????? > > Un abrazo a todos. > > Leonardo > Hola Leonardo: La prueba de Mann-Whitney también se conoce como la prueba de suma de rangos de wilcoxon y puede calcularse mediante la función wilcox.test Un saludo, Nicolás Benítez Parejo Técnico de Evaluación e Investigación Agencia

Dear Stefan I need to apply a Mann Whitney test to my data, by applying a bootstrap, in R. Loonkig for an answer in internet I found your question to the R mailing list but I have not found the answer to your question. Please, could you help me? thank you very much in advance. Best regards Luciana

Hello, I am hoping someone could shed some light into the Wilcoxon Rank Sum Test for me? In looking through Stats references, the Mann-Whitney U-test and the Wilcoxon Rank Sum Test are statistically equivalent. When using the following dataset: m <- c(2.0863,2.1340,2.1008,1.9565,2.0413,NA,NA) f <- c(1.8938,1.9709,1.8613,2.0836,1.9485,2.0630,1.9143) and the wilcox.test command as

Probably, it's an obvious info, but I have not found anything in R FAQ concerning this feature/bug. The results of ks.test and wilcoxon.test (in the Mann-Whitney version, paired = 'FALSE') don't coincide with the results from the other statistical packages, e.g. Statistica, Medcalc, and (as for MW test) from the numerous online MW tests. E.g. Statistica p-value=0.0435353 Medcalc

Hello everyone, I'm having some trouble interpreting the results of a Wilcoxon (Mann-Whitney U) test. Hope you can help. This is the R script that I am running: a <- c(1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 2, 1, 5, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 1, 1) b <- c(1, 2, 1, 1, 2, 3, 2, 2, 1, 2, 1, 1, 1, 2) wilcox.test(a, b, alternative="t", mu=0, exact=FALSE, paired=FALSE) #1st

Hello, can someone please help me with coding a function for a bootstrap WMW test (package boot, R under Windows, version 1.6.2)?

Hello List, I'm trying to prepare some lecture notes on non parametric methods, and I can't manually reproduce the results of the wilcox.test function for ordinal data. The data I'm using are from David Howell's website, available here http://www.uvm.edu/~dhowell/StatPages/More_Stuff/OrdinalChisq/OrdinalChiSq.html If I run the wilcox.test function on the data I get a p-value of

Hi, Could anyone provide the formula of the statistics which the wilcox.test used for the two-sample rank-sum test? I got some statistics of 0 values, but it is impossible to have 0 "rank-sum". Does the function use the Mann-Whitney U test statistics? Thanks. Ting-Yuan Liu

On 06/30/2013 02:14 AM, Anton Korobeynikov wrote: > Hi Tobi, > > First of all, all this is http://llvm.org/bugs/show_bug.cgi?id=1367 :) > >> The statistical test ministat is performing seems simple and pretty >> standard. Is there any reason we could not do something similar? Or are we >> doing it already and it just does not work as expected? > The main problem

I have been examining the Mann-Whitney test closely. And there are two features of the R implementation that puzzles me. The test statistic is reported as "W" and depends on the order of the arguments to the function. > x <- c(1,3,5,7,9) > y <- x-1 > x [1] 1 3 5 7 9 > y [1] 0 2 4 6 8 > wilcox.test(x, y)$statistic W 15 > wilcox.test(y,x)$statistic W 10