Bayes' theorem
Statement
Let be a probability space and let with and . Then
Remarks
Let be a finite or countable partition of into events of positive probability. With the law of total probability, . In Bayesian language, is the prior probability, is the likelihood and is the posterior probability. The proof: both and are equal to .
History
The theorem is named after Thomas Bayes. Pierre-Simon Laplace found it independently and developed it further.
Reading path
To understand this page from the ground up, read these 39 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Construction of the reals from Cauchy sequences concept
- Element definition
- Integers object
- Ordered field definition
- Proposition concept
- Random experiment concept
- Rational numbers object
- Set definition
- Ring of integers statement
- Conjunction definition
- Disjunction definition
- Implication definition
- Predicate definition
- Empty set object
- Family of sets definition
- Intersection definition
- Union definition
- Sample space definition
- The rationals form a field statement
- Existential quantifier definition
- Universal quantifier definition
- Disjoint sets definition
- Subset definition
- Union of a family of sets definition
- The rationals form an ordered field statement
- Universal set definition
- Partition of a set definition
- Power set definition
- Order on the reals definition
- Complement definition
- Interval definition
- Sigma-algebra definition
- Event definition
- Probability axioms concept
- Probability measure definition
- Probability space definition
- Conditional probability definition
- Law of total probability statement
- Bayes' theorem statement
Where this leads
17 pages build on this one.
- Prior probability
- Base rate fallacy
- Bayesian inference
- Posterior probability
- Monty Hall problem
- Bernstein–von Mises theorem
- Empirical Bayes method
- Bayes factor
- Lindley's paradox
- Bayes estimator
- Bayes risk
- Credible interval
- Jeffreys prior
- Bayesian hierarchical model
- Conjugate prior
- Shrinkage estimator
- Particle filter
Further reading
- Web https://en.wikipedia.org/wiki/Bayes'_theorem, Statement of theorem
About this page
| Tag | 0NM6E9VW04 |
|---|---|
| URI | m2://0NM6E9VW04 |
| Aliases | bayes-rule, bayes-law, bayes-formula |
| Kind | statement, theorem |
| Writing | W1 stated |
| MSC | 62F15 |
| Status | This copy of the site has no build data. Run m2 status 0NM6E9VW04. |
| Uses | Conditional probability, Law of total probability |
| Same as |
Markdown · JSON · Edit on GitHub
What this page needs for W2
- edge about out: the concepts that the statement is about (0 of 1)
- edge proves in: at least one proof node (0 of 1)
- edge instance_of or illustrates in: one example that shows the statement at work (0 of 1)
- explanation L2 (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.