glsnow wrote >>From your question it is not clear what your question/concerns really are, > and from what we can see it could very well be that you do not understand > the statistics that you are computing (not just the R implementation). We > ask for a reproducible example because that helps us to help you, just a > couple of boxplots let us make some guesses, but we do not know the data > values or even the means and standard deviations, even the actual sample > sizes could help. > >>From the graph it is not surprising that the wilcox test say that the 2 > groups are different and that the t test says that they are not (but > knowing data values would help even more). The 2 tests are testing very > different hypotheses. The wilcox test is testing that the 2 distributions > are identical and the more specific way it tests that is by looking at all > possible pairs between the 2 groups and seeing what proportion of them > have > each group higher, if the null were true then half the time the data point > from mixed would be higher than the data point from monoculture and half > the time the other way. From the boxplot we can see that the median of > monoculture is below the 1st quartile of mixed, so it is not surprising at > all that the wilcox test rejects the null hypothesis. > > The t-test (which version you used you do not say) is testing if the means > are equal, since monculture is clearly skewed to the right with potential > outliers, it would not be surprising if the sample means were close enough > to each other that the t-test does not see a significant difference. The > 2 > tests give different answers because they are answering very different > questions. > > You state that "I am not allowed to perform it" referring to the t-test. > This indicates that you don't have a full understanding or appreciation > of > the Central Limit Theorem (an important enough theorem that I have a > cross-stitch based on it hanging on my wall (along with 2 other > cross-stitches of Bayes theorem and the mean value theorem of > integration)). The plot shows 18 outliers in the monoculture group which > implies a sample size of at least 72, which means the other group has a > sample size of at least 14 if I interpret "five times as big" correctly. > This is a large enough sample size for the CLT to tell us the t-test will > give a reasonable approximation (provided the other assumptions hold > reasonably well and you are interested in the question being answered). > > So, I believe that the advice to read a textbook, or otherwise get some > help in basic understanding of the statistical tools is reasonable. Once > you have that, then if you still need help then give us a reproducible > example and make it clear what your question really is and you will be > much > more likely to receive an answer.
Thank you for your answer. It was actually really helpful. I apologize for the inadequate information, but I can see that I do really need to gather more statistical knowledge. -- View this message in context: http://r.789695.n4.nabble.com/Comparing-two-groups-tp4678190p4678510.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
