Thanks, Roger, your demo is interesting. I'm thinking about improving it later.
I've also made a demo for the CLT in my package 'animation', in which there's also normality testing for the sample means, because I don't think "bell-shaped" alone means normality - so I performed the Shapiro-Wilk test and plotted the P-values under the demo. See the function clt.ani() in the package 'animation', or http://animation.yihui.name/prob:central_limit_theorem You can use any function to denote the population (specify the argument 'FUN') in clt.ani(). Regards, Yihui -- Yihui Xie <[EMAIL PROTECTED]> Phone: +86-(0)10-82509086 Fax: +86-(0)10-82509086 Mobile: +86-15810805877 Homepage: http://www.yihui.name School of Statistics, Room 1037, Mingde Main Building, Renmin University of China, Beijing, 100872, China On Thu, Oct 16, 2008 at 4:22 AM, roger koenker <[EMAIL PROTECTED]> wrote: > Galton's 19th century mechanical version of this is the quincunx. I have a > (very primitive) version of this for R at: > > http://www.econ.uiuc.edu/~roger/courses/476/routines/quincunx.R > > > url: www.econ.uiuc.edu/~roger Roger Koenker > email [EMAIL PROTECTED] Department of Economics > vox: 217-333-4558 University of Illinois > fax: 217-244-6678 Champaign, IL 61820 > > > >> Jörg Groß wrote: >>> >>> Hi, >>> >>> >>> Is there a way to simulate a population with R and pull out m samples, >>> each with n values >>> for calculating m means? >>> >>> I need that kind of data to plot a graphic, demonstrating the central >>> limit theorem >>> and I don't know how to begin. >>> >>> So, perhaps someone can give me some tips and hints how to start and >>> which functions to use. >>> >>> >>> >>> thanks for any help, >>> joerg >>> > ______________________________________________ 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.
