Definition

Noun: - Bayes' postulate: In statistics, this is the principle that when applying Bayes' theorem, if the prior probabilities of different possible causes are unknown, they may be assumed to be equal. This is sometimes described as postulating an initial state of equal ignorance or the equidistribution of ignorance.

Usage

• Noun:
  • The researcher applied Bayes' postulate to initialize the model, assuming equal prior probabilities for all hypotheses.
  • A common criticism of Bayes' postulate is that the assumption of equal priors may not always be justified by real-world knowledge.

Advanced Usage

• "to invoke Bayes' postulate": to apply or use this principle of assuming equal prior probabilities.
  • In the absence of historical data, the analyst chose to invoke Bayes' postulate.

Variants and Related Words

• Bayesian inference (n): A method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available.
• Prior probability (n): In Bayesian statistics, the probability of an event before new data is considered.
• Equidistribution of ignorance (n): An alternative term for the concept underlying Bayes' postulate.

Synonyms

• Principle of indifference: A rule for assigning epistemic probabilities, stating that in the absence of any relevant evidence, agents should distribute their credence equally among all the possible outcomes.

Related Phrases

• Flat prior: In Bayesian statistics, a prior probability distribution that assigns equal probability to all possibilities, often resulting from applying Bayes' postulate or the principle of indifference.

Noun

1. (statistics) the difficulty of applying Bayes' theorem is that the probabilities of the different causes are seldom known, in which case it may be postulated that they are all equal (sometimes known as postulating the equidistribution of ignorance)