Solution
= Solution
A statistic $T(X)$ is sufficient for a parameter $\theta$ when the conditional distribution of the full sample $X$ given $T$ does not depend on $\theta$. For a dominated model, the <Fisher-Neyman factorization theorem> says this is equivalent to a factorization
$$
p_\theta(x)=g_\theta(T(x))h(x),
$$
where $h$ is independent of $\theta$.