## Programme to simulate from a Bernoulli and Binomial distribution

library(MASS)

p = 0.3	# probability of succes
n = 10000 # number of samples 

## Simulate from Bernoulli distribution
u = runif(n)

simBer = as.numeric(u < p)

hist(simBer)
sum(simBer)


## Simulate from Binomial distribution
N = 20 # total number of trials
# use the in-build function of R
simBin = rbinom(n, size=N, prob=p)
# simulate yourself
simBin_manual = rep(NA, n)
for(i in 1:n){
  u = runif(N)
  simBin_manual[i] = sum(u < p)
}

par(mfrow=c(1,2))
hist(simBin, ylim=c(0, 0.25), freq=FALSE)
hist(simBin_manual, ylim=c(0, 0.25), freq=FALSE)