Stirling approximation
Named by 2 essays across 2 fields — each of them below, with the objects they name alongside it.
The constant that counts what does not happen
Nothing grows in a shuffled pack of cards, and nothing grows in a factorial. Yet e sits in the middle of both — as the chance that a shuffle leaves nothing in place, and as the base that makes n! nearly a power.
What not knowing the coin costs
Kelly's rule stakes the edge, and the edge is the one thing a bettor never has. Estimate it from twenty tosses and stake the estimate, and a lucky start can turn a favourable coin into certain ruin. Learn it toss by toss instead, with Laplace's rule, and the cost of ignorance shrinks to a factor of about the square root of the number of tosses — because a bettor who learns is exactly a bettor who split the money among every fixed fraction at once.
Named alongside it
The objects these essays reach for when they reach for this one.
ApproximationBayes' theoremBeta distributionCounting argumentDerangemente, the numberEstimatorExpectationFactorialInclusion exclusionLaw of large numbersLimit