The Fisher information in an observation about a scalar parameter
is the variance of the score function. If
has probability
density function
,
it is
where
denotes the expectation value of
under the distribution with parameter
. Under regularity conditions that permit differentiation
under the integral sign, this can also be written as
Fisher information is additive for independent observations. Thus, independent observations from the same distribution have information
.
The reciprocal of the information gives the Cramér-Rao
bound on the variance of an unbiased estimator
under corresponding regularity conditions.