At some point a statistician will come head-to-head with the Fisher information, which measures the "information" about a population parameter contained in an observable random variable X.
It is the expected value of the observed information (sounds a bit like "maximum likelihood", right?).
Formally it is what statisticians call the "variance of the score".
The notion of "score" is something quite peculiar and distinctive to this branch of mathematics and is also known as the "informant". It is the rate of change of the log likelihood function of the population parameter, with respect to the parameter.
It is named after British polymath, Sir Ronald Aylmer Fisher, FRS.
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