Utilizing its namesake's theorem, which relates the conditional probability and its inverse, and first discussed in the 1763 essay "Towards Solving a Problem in the Doctrine of Chances," for 10 points, name this statistical method named after an English Presbyterian minister.
For this statistical approach, even if the parametric space usually labeled omega is zero, and thus a singleton, hypothesis testing can still proceed if one assigns a positive probability to pi sub naught, for the simple hypothesis. In this statistics, one can choose a prior density giving equal weight to all possible values of theta, in the case where little information can be obtained regarding past events, which are known as non-informative priors. The central feature of this statistical approach is the synthesis of the prior distribution and current sample data into a posterior probability distribution. Utilizing its namesake's theorem, which relates the conditional probability and its inverse, and first discussed in the 1763 essay "Towards Solving a Problem in the Doctrine of Chances," for 10 points, name this statistical method named after an English Presbyterian minister.
For this statistical approach, even if the parametric space usually labeled omega is zero, and thus a singleton, hypothesis testing can still proceed if one assigns a positive probability to pi sub naught, for the simple hypothesis.
{Bayesian} statistics