Learning

Sufficient Statistics and the Factorization Theorem

Probability Spaces and Random Variables → Sufficiency and Point Estimation

This graduate-level path builds a rigorous understanding of sufficient statistics, the factorization theorem, and minimal sufficiency. It starts from foundational probability and statistical inference concepts, then develops the formal theory, including the Neyman-Pearson factorization, exponential families, and minimal sufficient statistics, with applications to point estimation.