Hi Ted: Thanks for your prompt reply and explanation. That's what I was wondering, why would one need to test mu=0 ,which is the t.test default. But reading Peter Dalgaard's book and looking at some examples online, I saw t.test being used like that; t.test(datasetname) with no other arguments.
> > t.test(fishlength) > > One Sample t-test > > > > data: fishlength > > t = 30.1741, df = 13, p-value = 2.017e-13 > > alternative hypothesis: true mean is not equal to 0 > > 95 percent confidence interval: > > 36.14141 41.71573 > > sample estimates: > > mean of x > > 38.92857 > > > > Thanks in advance for your help. > > In terms of interpreting a statistical test, using your > data, > of the hypothesis that the mean length in the population is > 0, > the P-value of 0.0000000000002017 is very strong evidence > indeed > that the mean is not 0. > > However, I do not know why you are asking the question. No > test > is needed. The length of any living fish, even while it is > still > in the egg, is greater than 0; and whatever population you > have > taken your sample from will have a mean length which is > greater > than 0. > > That is not to say that the result of a t-test on any > sample > will necessarily give a significant result. You could have > a > small catch with lengths, say, > > fishlengths <- c(2,4,9,20,50) > t.test(fishlengths,mu=0) > > # One Sample t-test > # data: fishlengths > # t = 1.9273, df = 4, p-value = 0.1262 > # alternative hypothesis: true mean is not equal to 0 > # 95 percent confidence interval: > # -7.489442 41.489442 > # sample estimates: > # mean of x > # 17 > > And all you can conlude from that is that the sample, *in > itself*, > does not carry sufficient information to confirm what you > know > is true (i.e. mu > 0). Even the one-sided test of mu=0 > with alternative > alt="greater" does not give a result significant > at 5%: > > t.test(fishlengths,mu=0,alt="greater") > > # One Sample t-test > # data: fishlengths > # t = 1.9273, df = 4, p-value = 0.0631 > # alternative hypothesis: true mean is greater than 0 > # 95 percent confidence interval: > # -1.803807 Inf > # sample estimates: > # mean of x > # 17 > > Hoping this helps! > Ted. ______________________________________________ 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.
