Choosing the best estimator Given yield measurements $X_1,X_2,X_3$ from three independent runs of an experiment with variance $\sigma^2$, which is the better of the two estimators:
$\hat\theta_{1}$= $\frac{X_1+X_2+X_3}{3}$,                  $\hat\theta_{2}$=$\frac{X_1+2X_2+X_3}{4}$
I know that in order to find the best estimator if both are unbiased, we are supposed to choose the one with the smallest variance.  I need help just starting this problem.  Thank you.

Variance of the Sample mean estimate is just $$\text{VAR}(\bar{\mu})=\text{VAR}\left(\frac{\sum_i X_i}{n}\right)$$ for the first case and $$\text{VAR}(\bar{\mu_2})=\text{VAR}\left(\frac{X_1+X_2+X_2+X_3}{4}\right)$$ in the second. Now apply scaling property of variances to see which one has a higher variance. 
