## BAYESIAN METHOD

We have stated earlier that the goal of statistical inference is not merely to obtain an estimator but to be able to say, using the estimator, where the true value of the parameter is likely to lie. This is accomplished by constructing confidence intervals, but a shortcoming of this method is

that confidence can be defined only for a certain restricted sets of intervals. In the Bayesian method this problem is alleviated, because in it we can treat a parameter as a random variable and therefore define a probability distribution for it. If the parameter space is continuous, as is usually the case, we can define a density function over the parameter space and thereby consider the probability that a parameter lies in any given interval...