> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Zembower, Kevin > Sent: Wednesday, October 31, 2007 12:57 PM > To: r-help@r-project.org > Subject: [R] Homework help: Is this how CIs of normal > distributions are computed? > > I'm looking for a function in R similar to t.test() which was > generously > pointed out to me yesterday, but which can be used for normally > distributed data. > > To recap yesterday: > > x <- scan() > 1: 62 52 68 23 34 45 27 42 83 56 40 > 12: > Read 11 items > > alpha<- .05 > > t.test(x) > > One Sample t-test > > data: x > t = 8.8696, df = 10, p-value = 4.717e-06 > alternative hypothesis: true mean is not equal to 0 > 95 percent confidence interval: > 36.21420 60.51307 > sample estimates: > mean of x > 48.36364 > > What if I now mock-up my data for 100 trials: > > x100<-sample(x, 100, replace=TRUE) > > I think that I should be able to use a normal distribution, because of > the n>30 rule-of-thumb. > <<<snip>>>
You could probably use the Normal distribution as an approximation under these circumstances, but why would you when you have a more accurate CI using t.test? Dan Daniel J. Nordlund Research and Data Analysis Washington State Department of Social and Health Services Olympia, WA 98504-5204 ______________________________________________ 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.