Sublime

statistical comparisons may be made strictly in terms of the interior variation in the data,

given a number of observations, you can actually gain information by throwing information away!

In the early eighteenth century it was discovered that in many situations the amount of information in a set of data was only proportional to the square root of the number n of observations, not the number n itself.

it being taken for granted that at least one other hypothesis (Divine Providence or Newtonian dynamics) would yield a much higher probability for the observed data than the probability found under a hypothesis of “chance.”

Granted that more evidence is better than less, but how much better? For a very long time, there was no clear answer.

In even approximate equilibrium, the variability Darwin both required and demonstrated existed was in conflict with the observed short-term stability in populations.

The second pillar, Information Measurement, is logically related to the first: If we gain information by combining observations, how is the gain related to the number of observations?

statistical comparisons do not need to be made with respect to an exterior standard but can often be made in terms interior to the data themselves.

He computed exactly what the inclination of the chutes must be (he called it a coefficient of reversion) in order for intergenerational balance to be preserved,