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The inverse moments in part i giveThus the bias is positive, and direct expansion of the mean squared error yieldsFor comparison, the variance is $n^2{\theta }^2/[(n-1{)}^2(n-2)]$; adding the squared bias gives the same answer by the bias-variance decomposition.