Monte Carlo, Markov Chains, Metropolis Hastings.
for Uniform(0,1). Note U(0,1) equals Beta(1,1). Prior distribution Likelihood Likelihood is the probability of getting certain data when p(Head) =θ, written as p(data|θ). It is determined by the distribution of the data. In this case, I repeatedly toss my coin for 10 times, and record head and tail