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,

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?

In order to make the case for evolution by natural selection, it was essential to establish that there was sufficient within-species heritable variability:

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.

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

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.

Clearly the calculation of a single probability is not the answer to all questions. A probability itself is a measure and needs a basis for comparison. And clearly some restriction on allowable hypotheses is needed, or else a self-fulfilling hypothesis such as “the data are preordained” would give probability one to any data set.