bayes' theorem: meaning, definition, pronunciation and examples

C2
UK/ˈbeɪz ˈθɪərəm/US/ˈbeɪz ˈθiːrəm/

Technical / Academic

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Quick answer

What does “bayes' theorem” mean?

A theorem in probability theory that describes how to update the probability of a hypothesis based on new evidence.

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Pronunciation

Definition

Meaning and Definition

A theorem in probability theory that describes how to update the probability of a hypothesis based on new evidence.

A mathematical formula expressing the conditional probability of an event, given prior knowledge of conditions that might be related to the event. It provides a principled way to incorporate new data to revise prior beliefs, forming a cornerstone of Bayesian statistics, machine learning, and decision theory.

Dialectal Variation

British vs American Usage

Differences

No significant difference in meaning or usage. The possessive apostrophe (Bayes') is standard in both varieties.

Connotations

Identical technical connotations in statistics, data science, and philosophy of science.

Frequency

Equally low frequency in general discourse but equally high frequency in specialised academic and technical contexts.

Grammar

How to Use “bayes' theorem” in a Sentence

apply Bayes' theorem to + [a problem/data]update + [probability/belief] using Bayes' theoremcalculate + [posterior probability] with Bayes' theorem

Vocabulary

Collocations

strong
apply Bayes' theoremusing Bayes' theoremaccording to Bayes' theoremderive Bayes' theorem
medium
understand Bayes' theoremformula of Bayes' theoremconcept of Bayes' theorembased on Bayes' theorem
weak
simple Bayes' theoremfamous Bayes' theoremstatistical Bayes' theorem

Examples

Examples of “bayes' theorem” in a Sentence

adjective

British English

  • The Bayesian approach is derived from Bayes' theorem.
  • She offered a Bayesian analysis of the results.

American English

  • The Bayesian framework relies on Bayes' theorem.
  • He is known for his Bayesian models in machine learning.

Usage

Meaning in Context

Business

Used in risk analysis, forecasting, and machine learning applications for marketing or fraud detection.

Academic

Central to statistics, data science, machine learning, philosophy of science, and psychology (e.g., modelling cognition).

Everyday

Virtually never used in casual conversation, except in a pedagogical or popular science context.

Technical

The foundational tool for Bayesian inference, used in algorithms from spam filtering to medical diagnostics.

Vocabulary

Synonyms of “bayes' theorem”

Neutral

Bayes' ruleBayesian update rule

Weak

Bayesian formulaprobability update formula

Watch out

Common Mistakes When Using “bayes' theorem”

  • Misspelling as 'Baye's theorem', 'Bayse theorem', or 'Bayesian theorem' (which is related but not the same).
  • Incorrectly using it as a verb, e.g., 'We need to bayes this data.'
  • Omitting the required apostrophe.

FAQ

Frequently Asked Questions

The Reverend Thomas Bayes (c. 1701–1761), an English statistician, philosopher, and Presbyterian minister.

Bayesian statistics uses Bayes' theorem to incorporate prior beliefs with evidence, treating probability as a degree of belief. Frequentist statistics interprets probability solely as the long-run frequency of events, without incorporating prior probabilities.

Yes. A medical test for a rare disease: Bayes' theorem is used to calculate the actual probability a patient has the disease, given a positive test result, by considering the test's accuracy and the disease's rarity (prior probability).

No. While mathematical, its principles of updating beliefs are applied in fields like machine learning (spam filters), psychology (models of learning), law (probabilistic evidence), and economics (decision-making).

A theorem in probability theory that describes how to update the probability of a hypothesis based on new evidence.

Bayes' theorem is usually technical / academic in register.

Bayes' theorem: in British English it is pronounced /ˈbeɪz ˈθɪərəm/, and in American English it is pronounced /ˈbeɪz ˈθiːrəm/. Tap the audio buttons above to hear it.

Learning

Memory Aids

Mnemonic

Bayes' theorem updates your belief (prior) with new evidence to get a revised belief (posterior). Think: 'Before Evidence' -> 'After Evidence, Updated'.

Conceptual Metaphor

UPDATING A MAP (Prior belief is an old map, new evidence is fresh survey data, posterior is the updated, more accurate map).

Practice

Quiz

Fill in the gap
The key to Bayesian statistics is the ability to .
Multiple Choice

Bayes' theorem is fundamentally used to: