Past exam of the mathematics course of the University of Cambridge / 2018 / iii / Paper 219 / 1 / i

Linearity of expectation gives ${\mathbb{E}}_{\mu }[\hat{\mu }]=({\alpha }_1+{\alpha }_2)\mu$. Thus a linear unbiased estimator for every value of the distance modulus satisfies $\boxed{{\alpha }_1+{\alpha }_2=1}$. Requiring unbiasedness at the single value $\mu =0$ would not impose this constraint; an unbiased estimator must work throughout the parameter space.