bayes-sequential-updating-rule
IN premise — summaries/2026/08/24/wiki-Bayesian_inference-chunk-1.md
Created 2026-08-25T02:58:42+00:00
In Bayesian sequential updating, the posterior from one round of evidence becomes the prior for the next round, and for i.i.d. observations the likelihoods multiply.
Summary
As new evidence arrives, you don't restart the analysis from zero; instead, your updated picture of what is most likely after each observation is exactly the starting point for the next one. This makes the system's knowledge build incrementally and in any order, so each new data point just layers on top of what was already learned rather than forcing a full recompute.