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Glossary · Probability

Law of large numbers

The law of large numbers states that as the number of independent trials grows, the average of the results converges to the expected value, while the absolute counts of each outcome need not even out.

Law of large numbers, in full

Category
Probability
Also called
LLN, Bernoulli's theorem
In the glossary
All 75 terms, A–Z

A worked example

The same idea with real numbers attached.

Roll a fair d6. Its expected value is (1+2+3+4+5+6)/6 = 3.5. After 60 rolls you might see six come up 6 times against an expectation of 10, a shortfall of 4, which is 10 percent of rolls against an expected 16.67 percent. After 6,000 rolls the shortfall might be 40, ten times larger, yet 960 sixes out of 6,000 is 16.0 percent, ten times closer to target.

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Where it comes up on this site

Law of large numbers: frequently asked

Only as a proportion. The share of heads approaches 0.5, while the raw difference between the two counts typically drifts further from zero the longer you flip. Both hold at once because the gap grows roughly with the square root of n and the total grows with n, so dividing one by the other sends the imbalance to nothing even as the imbalance itself gets bigger. Nothing corrects anything. The denominator just wins.

There is no threshold. Cutting the wandering in the proportion by a factor of ten takes a hundred times as many trials.

It says the long-run average return per ticket approaches the game's expected value, which is negative. About any single ticket it says nothing.

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Lottery mechanics, probability, numerology and astrology, defined in one A–Z.

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