In short
Updating your belief about something as new evidence arrives, using Bayes' theorem — a mindset (not just a formula) that's especially useful for reasoning about model confidence and rare events.
How to learn this
- 1Work through a classic Bayesian update example (like the medical test false-positive problem).
- 2Learn the difference between a prior, a likelihood, and a posterior in plain language.
- 3Practice updating a belief step by step as you're given new pieces of evidence.
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