• bayesian statistics treats parameters as a random variable + updates prior distributions to get a posterior
• classical statistics treats parameters as fixed but unknown

does not having a prior mean paramter treated in classical way

• bayesian statistics always requires a prior
• you may want to consider non informative priors to minimise the influence on the posterior