Bayesian statistics requires some form of prior. Sometimes this is based on past data or is in the form of a researcher's beliefs encoded as a probability, but where there are no clear grounds for either of these, default Bayesian factors may be used. Typically this will be a uniform distribution over bounded values: for example, assigning a prior probability of 1/6 for each of the potential faces of a die. In the case of unbounded data the Cauchy distribution is a frequent default choice although this also requires a central value and spread parameter.
Also used in hcistats2e: Chap. 7: page 86
Used in glossary entries: bounded data, Cauchy distribution, encoding (belief) as probability, unbounded data, uniform distribution