Concept

Normal distribution

The bell-shaped distribution that sums of many small independent contributions settle into.

Named by 4 essays across one field — each of them below, with the objects they name alongside it.

1173760121153109683661left or right, 12 times, 600 times over

A bell curve assembled out of coin flips

Drop six hundred balls through a board of pegs, each bouncing left or right at random, and they pile up in a shape that can be predicted precisely. Nothing coordinated them.

probability · central limit
050100150200250300350400-60-40-20204060steps takendistance from the start√n

A walk that always comes home, until it does not

Step left or right at random, forever, and the walk returns to where it started with certainty. On a grid it also returns. In space it does not, and about a third of walks leave and never come back.

probability · random walk
-6-4-202460.000.100.200.300.400.50valueprobability1.5σthe meanmean 0.300, standard deviation 1.847; beyond 1.5 of them lies 0.2000 against a bound of 0.4444, beyond 2 ofthem lies 0.1000 against a bound of 0.2500, beyond 3 of them lies 0.0000 against a bound of 0.1111the bound knows only the variance — not the shape, not the number of values, not whether the distribution issymmetric — which is why it is so far from tight here and cannot be improved in general

How far from the average a thing can be

Knowing only an average and a spread — nothing about the shape, nothing about the number of outcomes, nothing about symmetry — the chance of landing three standard deviations out is at most one in nine. And there is a distribution that lands there exactly that often, so the bound cannot be improved.

probability · concentration
-1-0.50.510.01.02.03.0the average, minus the meann = 4n = 16n = 64-3-2-11230.00.10.20.30.4the sum, minus n means, over √nn = 4n = 16n = 64the same exact distributions, drawn twice as densities: divided by n the spread falls 0.500 → 0.250 →0.125, divided by √n it is 1.000 every timeso the left curves climb — 0.75 → 1.57 → 3.18 at the peak — and the right ones settle on 0.399, which is theheight of the bell curve

The average settles and the wobble does not

Two theorems are usually met a page apart and sound as though one is a sharper version of the other. They are the same sums looked at through two different magnifying glasses: divide by the number of them and everything collapses to a point, divide by its square root and a shape appears.

probability · central limit

Named alongside it

The objects these essays reach for when they reach for this one.

ConvergenceIndependenceBinomial distributionConvergence rateExpectationHeavy tailsLimitRandom walkVarianceCentral limit theoremConcentration inequalityDiffusion

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