# rolling some die d <- sample(6, 10000, replace = TRUE) hist(d) # mean value mean(1:6) mean(d) # flipping coins numHeads <- sapply(1:1e5, function(x) { #print(x) c <- sample(2, 100, replace=TRUE) sum(c == 1) }) #View(numHeads) hist(numHeads, breaks=100, xlim=c(0,100)) # note - that is called a bernoulli distribution numHeads <- sapply(1:1e6, function(x) { rbinom(n=1, size=100, prob=0.5) }) #View(numHeads) hist(numHeads, breaks=100, xlim=c(0,100)) pbinom(q=30,size=100, prob=0.5)