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Markov Chain Monte Carlo used for posterior probability distribution prediction. Under the Bayesian paradigm, two algorithmic updating approaches are explored - one in which we know the parameters of the underlying distribution of our data, and one in which we don't know the parameters of the underlying distribution of our data.