Sublime

Laplace continued his research throughout France’s political upheavals. In 1810 he announced the central limit theorem, one of the great scientific and statistical discoveries of all time. It asserts that, with some exceptions, any average of a large number of similar terms will have a normal, bell-shaped distribution.

Where statistics becomes complicated, and fails us, is when we have distributions that are not symmetric, like the urn above. If there is a very small probability of finding a red ball in an urn dominated by black ones, then our knowledge about the absence of red balls will increase very slowly—more slowly than at the expected square root of n rate

Take TV as an example. Nielsen uses a dataset of 18,000 to 30,000 people to measure the viewing habits of 200 million plus Americans. In a world of fragmented consumption, no sophisticated math can account for all the inherent anomalies, and you are left with high-grade, nonrepresentative “data.”