similar to: median of two groups

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

The function 'wilcox.test' in R and S gives (almost) identical results (see below). 'qwilcox' however, does not: > qwilcox(p,5,5) p: 0.025 0.975 -------------------- R> 3 22 S> 18 37 I originally wanted to ask a questions, but then I found the answer. Given the confusion I run into, I wonder if this experience is worth reporting. The

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 <-

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

Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method

Dear R users, I am new to R and I would like to ask your help with the following topic. I have three sets of numeral data, 2 sets are paired and a third is independent of the other two. For each of these sets I have obtained their basic statistics (mean, median, stdv, range ...). Now I want to compare if these sets differ. I could compare the mean doing a basic T test . However, I was

Dear List, after updating the exactRanksumTests package I receive a warning that the package is not developed any further and that one should consider the coin package. I don't find the signed rank test in the coin package, only the Wilcoxon Mann Whitney U-Test. I only found a signed rank test in the stats package (wilcox.test) which is able to calculate the exact pvalues but unfortunately

Hi. I'm going to introduce the R-package for a group of medical doctors later this week and is a little confused about there use of a test named "willcoxon-pratt" for testing if the clinical and biochemical markers has decreased significantly after the use of some drugs for a group of patients. Looking into the R-functions I would in R recommand using a matched-pairs Wilcoxon

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

Hello, I use t.test for normal distributed and wilcox.test for non-normal distributed samples. It is easy to write a function for t.test that calculates the effect size, because all parts of the formula are available from the t.test result: r = sqrt(t*t / (t*t + df)) However, for Wilcoxon tests, the formula for effect sizes is: r = Z / sqrt(N) I wonder how I can calculate the Z-score in R for

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

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

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

Hi, I do want to use the Mann-Whitney test which ranks my data and then uses those ranks rather than the actual data. Here is the R code i am using: group1<- c(1.34,1.47,1.48,1.49,1.62,1.67,1.7,1.7,1.7,1.73,1.81,1.84,1.9,1.96,2, 2,2.19,2.29,2.29,2.41,2.41,2.46,2.5,2.6,2.8,2.8,3.07,3.3) > group2<-

Hello, I'm trying to compare the allozyme data from two taxa. I have several columns of data (19 loci) for each species. I want to do a Mann-Whitney U-test or the wilcox.test (two sample Wilcoxon). When I try to run my code (the first two columns are 1:name of the species, 2:name of individual) I get the error message: "Error in wilcox.test.default(CaScSc, CaScCo, alternative

Hi, I recently ran into the problem that I needed a Siegel-Tukey test for equal variability based on ranks. Maybe there is a package that has it implemented, but I could not find it. So I programmed an R function to do it. The Siegel-Tukey test requires to recode the ranks so that they express variability rather than ascending order. This is essentially what the code further below does. After the

Hi all, I have being using wilcox.test to test for differences between 2 independent samples. I had understood the difference in location to be conventionally the difference in the sample medians however this is not the case when implemented in R. I have tied ranks and therefore non-exact p-value and confidence intervals are calculated due to the normal approximation. But what exactly is this

I am sure I am opening myself up to looking stupid, but I have two samples with medians of 613.5 and 189 (difference in location of 424 compared to the difference suggested from the wilcoxon of 291.5) > wilcox.test(pipwtCount,pipwdCount, conf.int=TRUE, na.rm=TRUE) Wilcoxon rank sum test data: pipwtCount and pipwdCount W = 822, p-value = 0.01227 alternative hypothesis: true location

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

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