← Technical glossary
Definition

Bayesian regression

Regression that represents model parameters as probability distributions, combining prior information with observed data.

Why it matters

The practical consequence.

It makes uncertainty explicit and allows prior knowledge to be incorporated transparently instead of producing one falsely precise estimate.

Example

How it appears in a system.

A marketing model can estimate a range of likely channel effects rather than claiming one exact return on ad spend.

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