The probability of a parameter value at the start of an analysis.
The probability of an event before evidence is considered. Often, the prevalence of a disorder in a population.
The probability assigned to a statement before making an observation. cf. posterior probability. Such probabilities are usually construed to be epistemic.
The epistemic probability of a belief independent of (i.e., prior to) a specified piece of evidence. When considering, for example, the prior probability of something you heard, its prior probability is simply how probable it would be if you had not heard it.
A probability assigned to a propostion in the absence of any other information. Written P(A), it is also known as an unconditional probability.
The probability that an event occurs in a population, with no evidence about the current case in question. See: Bayes' Theorem.
The prior probability for a class label is the probability of seeing this label in the data for a randomly chosen record, ignoring all attribute values. Mathematically, this is the number of records with the class label divided by the total number of records. (See also Conditional Probability. Prevalence was called support in previous versions of MineSet.)
An assigned numerical value of from 0 - 1 (ranging from impossible to certain) of the non-genetic evidence used in evaluating paternity. It is estimated on the basis of the circumstances surrounding the event, e.g. casual acquaintance versus an intimate relationship. A prior probability of 0.5 is considered neutral and is an equal weighting of the nongenetic evidence for and against paternity.
A prior probability is a marginal probability, interpreted as a description of what is known about a variable in the absence of some evidence. The posterior probability is then the conditional probability of the variable taking the evidence into account. The posterior probability is computed from the prior and the likelihood function via Bayes' theorem.