Tier 3 · AdvancedFree
Decision Theory
Expected Value
8 modules~64 min totalVerifiable certificate on completion
Syllabus
01Expected Value and VarianceMath
11 min02The Kelly CriterionMath
11 min03Utility, Risk Aversion, and the Certainty EquivalentMath
12 min04The Kelly Bet
6 min05The Decision Tree
6 min06The Prior and the Shock
6 min07The Option to Wait
6 min08When EV Fails
6 minFrom Module 1 — read a sample
The expected value of a probability distribution is the 'center of gravity' — if you balanced all the possible outcomes on a seesaw weighted by their probabilities, EV is where it balances. Two gambles can share the same EV while one is nearly certain and the other swings wildly, which is why you need variance alongside the mean to make smart decisions.
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