# How to find the variance and bias to obtain MSE?

Considering $MSE[\hat{\mu}|{\mu}*]= Var [\hat{\mu}|{\mu}*] + Bias (\hat{\mu}|{\mu}*)^2$ and the following givens $\hat{\mu}= 112$, ${\mu}*= 112$, ${\mu}_0 = 100$, ${n = 10}$, $\bar{y}=113$, and ${\sigma^2} =225$, how do I determine the variance and bias to get my MSE? Any resources that would help facilitate an understanding of this would be great!

• can you define all of your notation, and possibly remove mentions of things you don't need? – Taylor Feb 8 '17 at 3:27

Bias is the expected difference between your estimate and the true value $\mu*$, variance is the expected squared difference between the estimate and its expectation.