Dear R-users! I´m faced with following problem: Given is a sample where the sample size is 12, the sample mean is 30, and standard deviation is 4.1. Based on a Student-t distribution i´d like to simulate randomly 500 possible mean values within a two-tailed 95% confidence interval. Calculation of the lower and upper limit of the two-tailed confidence interval is the easy part.
m <- 30 #sample mean s <- 4.1 #standard deviation n <- 12 #sample size quant <- qt(0.975,df=11)*s/sqrt(n)#student-t with two tailed )95% confidence interval l <- m-quant# lower limit h <- m+quant# upper limit 500 randomly simulated values are computable with the rt() command but this command does not consider the 95% confidence interval. Does somebody of you know, how i can overcome this problem? Best regards Thomas -- View this message in context: http://r.789695.n4.nabble.com/Student-t-distributed-random-value-generation-within-a-confidence-interval-tp4650561.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.
