A random variable is uniformly distributed over $(0,\theta)$. The maximum of a random sample of $n$, call $y_n$ is sufficient for $\theta$ and it is also the maximum likelihood estimator. Show also that a $100\gamma\%$ confidence interval for $\theta$ is $(y_n, y_n /(1 − \gamma )^{1/n})$.
Could anyone tell me how to deal with this problem? Do I have to use the central limit theorem?