On Tue, 30 Oct 2007, Zembower, Kevin wrote: > I'm trying to replicate some of the examples from my textbook in R (my > text uses Minitab). In this problem, I'm trying to construct a 95% > confidence interval for these distance measurements [1]: > > > # Case Study 7.4.1, p. 483 > > x <- scan() > 1: 62 52 68 23 34 45 27 42 83 56 40 > 12: > Read 11 items > > alpha<-.95 > > mean(x) + qt(c((1-alpha)/2, 1-((1-alpha)/2)), df=length(x)-1) * sd(x) > / sqrt(length(x)) > [1] 36.21420 60.51307 > > > > Are confidence intervals with the t distribution constructed using this > type of equation, or am I overlooking a more concise, 'canned' approach > that's already been programmed? Any suggestions on simplifying this?
R offers a confint() generic with methods for various types of models. If you consider estimation of the mean as a simple linear model (with only an intercept) you can do fm <- lm(x ~ 1) fm to estimate the mean and then confint(fm) to get the confidence interval (by default at 0.95 level). hth, Z > Thanks for all your advice and help. > > -Kevin > > [1] An Introduction to Mathematical Statistics and its Applications, > fourth ed., Larsen and Marx. > > Kevin Zembower > Internet Services Group manager > Center for Communication Programs > Bloomberg School of Public Health > Johns Hopkins University > 111 Market Place, Suite 310 > Baltimore, Maryland 21202 > 410-659-6139 > > ______________________________________________ > 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. > > ______________________________________________ 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.
