Hi all, I want to create a sample called x, with length 10 from a N(0,1) distribution. Next to that I want to create a sample called y, with length 10 from a N(0.5 ,1) distribution. Both samples are undergoing a t.test. The outcome must be that I can see how many times for x H0 was rejected. The same for y. I am testing under a confidence level of 0.05 Down below is the function I must use:
pv=function(n=10,N=100,m=1,...){ resx=numeric(N) resy=numeric(N) for (i in 1:N){ x=rnorm(n) y=rnorm(n,m) resx[i]=t.test(x,...)[[3]] resy[i]=t.test(y,...)[[3]] } z=list(resx,resy) names(z)=c("px","py") z} So I compute pv(10,100,0.5) which gives me p-values in px and py. But somewhere I must give a statement (I think at the ... but that gives me errors) that px<0.05 so I can see how many times H0 was rejected. Thus, the values that are computed must be compared with the statement <0.05. -- View this message in context: http://r.789695.n4.nabble.com/Function-for-testing-tp4634109.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.