Dear R helper, I have a statistic question. I have a vector of 500 values for which I need to assess the statistical significance of occurrence real.dist <- realValues For that, I sampled from my data large data pool 1000 other vectors of 500 values each. I then run ks.test with my real vec vs each of the sampled vectors. ks.res<-unlist(lapply(l.sampled,function(x){ ks <- ks.test(real.dist, x$dist) as.numeric(ks[["statistic"]]) })) I now have 1000 "D" values with their corresponding p.values. How can I have a general p.value saying that my real data differs from the sampled one, and thus significant ? Any suggestion ? Many thanks, -- View this message in context: http://r.789695.n4.nabble.com/comparing-real-set-vs-sampled-sets-tp4672709.html Sent from the R help mailing list archive at Nabble.com.