More formally, the following is the method employed. As mentioned above, statistics is concerned with the estimation of numerical quantities. In the Bayesian context, the quantities of interest will be random variables, and could, for example, be the proportion of rusted cars as referred to above. Before an experiment or survey, the prior knowledge about the quantities of interest are summarised in the form of a probability statement.
Denote the parameter or parameters of interest 
and the
state of current experiences to date is denoted H. Such
experience might be to do with knowledge of the material
properties of cars, the nature of the roads, the weather and
indeed knowledge of previous studies. The probability statement
about initial beliefs is denoted 
and is termed
the prior belief. Since this is a probability statement it takes
the form of a probability distribution and is often referred to as
the prior distribution, or more simply the prior.