In any case study, when we use Bayesian analysis to solve our problem we consider a model parameter which is sometimes known and sometimes unknown. And using this parameter(and of course prior data) we construct prior and posterior distributions for our model.
Can someone explain to me by giving example/s (may be a case study) what actually is this model parameter? What are its properties?