The Fisher-Neyman factorization theorem states that a statistic 
is a sufficient statistic for a parameter 
iff the probability
density function of the sample can be written
 |
for nonnegative functions 
and 
, where 
does not depend on 
.
The theorem converts the definition of sufficiency in terms of a conditional distribution into a factorization that can often be checked directly.
