Simple Metropolis: Normal Precision - Gamma . Suppose X=2 was observed from the population distributed as N(0,1/)and one wishes to estimate the parameter . (Here is the reciprocal of the variance ² and is called the precision parameter). Suppose the analyst believes that the prior on is Ga(1/2, 1). Using Metropolis algorithm, approximate the posterior distribution and the Bayes' estimator of . As the proposal distribution, use gamma Ga(,) with parameters , selected to ensure efficacy of the sampling. Please provide step by step explanation.