I'm trying self-study some inference and now I'm trying to understand how to solve some problems on this topic but I found this basic problem that I'm not being able to solve.
Problem:
Let $X_{1},...,X_{n}$ i.i.d $f(x | \theta)$, where $f(x | \theta) = \theta x ^{\theta -1 }$.
Is $\sum_{i}^{n} X_{i}$ a sufficent statistic for $\theta$? How can I find a complete sufficient statistic?
Im really confused actually. I know these problems can be solved with the factorization theorem, so we have that $f(x_{1},...,x_{n} | \theta) = \prod \theta x_{i} ^{\theta -1} = \theta ^{n} \prod x_{i}^{\theta} \prod x_{i}^{-1}$, then $h(x) = \prod x_{i} ^{-1}$ and $g[\theta,T(x_{i})] = \theta^{n}\prod x_{i}^{\theta}$. So in this case $T(x_{1},...,x_{n}) = \prod x_{i}$ is a sufficient statistic right?
But I don't know hot to check if $\sum X_{i}$ is in fact a suff. statistic and I don't know how to prove that the statistic I found is complete.