Estimating parameters by frequentist and Bayesian approaches

Frequentists estimate parameters by choosing the value that maximises the likelihood of the data. The Bayesian approach assumes that the unknown value of a parameter is drawn from a prior distribution and it can be estimated by the mean of the distribution of the parameter conditional on the data. The Bayesian approach is often superior if a rational prior distribution is known.