bayes' theorem Antonyms

No Synonyms and anytonyms found

Meaning of bayes' theorem

Wordnet

bayes' theorem (n)

(statistics) a theorem describing how the conditional probability of a set of possible causes for a given observed event can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause

bayes' theorem Sentence Examples

  1. Bayes' theorem is a fundamental concept in probability theory that allows us to update our beliefs based on new evidence.
  2. Bayesians argue that Bayes' theorem provides a rational framework for making decisions under uncertainty.
  3. The probability of a hypothesis given the evidence, P(H|E), is calculated using Bayes' theorem as P(H|E) = P(E|H) * P(H) / P(E).
  4. Bayes' theorem is particularly useful in situations where we have prior knowledge or assumptions about the problem at hand.
  5. In medical diagnostics, Bayes' theorem can be employed to calculate the probability of a patient having a disease based on the results of a diagnostic test.
  6. Bayes' theorem is widely applied in machine learning, where it forms the basis of Bayesian classifiers and other probabilistic models.
  7. The use of Bayes' theorem has sparked debates regarding its role in scientific reasoning and the foundations of probability.
  8. Bayes' theorem is a powerful tool for reasoning about uncertain events, providing a systematic approach to updating our beliefs.
  9. Critics of Bayes' theorem argue that the choice of prior probabilities can be subjective and can influence the outcome of the calculation.
  10. Despite its limitations, Bayes' theorem remains a highly influential concept in probability theory with numerous applications in various fields.

FAQs About the word bayes' theorem

(statistics) a theorem describing how the conditional probability of a set of possible causes for a given observed event can be computed from knowledge of the p

No synonyms found.

No antonyms found.

Bayes' theorem is a fundamental concept in probability theory that allows us to update our beliefs based on new evidence.

Bayesians argue that Bayes' theorem provides a rational framework for making decisions under uncertainty.

The probability of a hypothesis given the evidence, P(H|E), is calculated using Bayes' theorem as P(H|E) = P(E|H) * P(H) / P(E).

Bayes' theorem is particularly useful in situations where we have prior knowledge or assumptions about the problem at hand.