> -----Original Message----- > From: [EMAIL PROTECTED] [SMTP:[EMAIL PROTECTED] On Behalf Of Adaikalavan > Ramasamy > Sent: Thursday, November 10, 2005 10:31 AM > To: Duncan Murdoch > Cc: r-help@stat.math.ethz.ch > Subject: Re: [R] How to find statistics like that. > > If my usage is wrong please correct me. Thank you. > > Here are my reason : > > 1. p-value is a (cumulative) probability and always ranges from 0 to 1. > A test statistic depending on its definition can wider range of possible > values. > > 2. A test statistics is one that is calculated from the data without the > need of assuming a null distribution. Whereas to calculate p-values, you > need to assume a null distribution or estimate it empirically using > permutation techniques. > > 3. The directionality of a test statistics may be ignored. For example a > t-statistics of -5 and 5 are equally interesting in a two-sided testing. > But the smaller the p-value, more evidence against the null hypothesis. > > Regards, Adai > -------- Hi: A statistic is any real-valued or vector-valued function whose domain includes the sample space of a random sample. The p-value is a real-valued function and its domain includes the sample space of a random sample. The p-value has a sampling distribution. The code below, found with Google ("sampling distribution of the p-value" "R command") shows the sampling distribution of the p-value for a t-test of a mean when the null hypothesis is true. Ruben
n<-18 mu<-40 pop.var<-100 n.draw<-200 alpha<-0.05 draws<-matrix(rnorm(n.draw * n, mu, sqrt(pop.var)), n) get.p.value<-function(x) t.test(x, mu = mu)$p.value pvalues<-apply(draws, 2, get.p.value) hist(pvalues) sum(pvalues <= alpha) [1] 6 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html