To prove that mean quadratic error of a parameter is the sum of varianca of parameter and quadratic B of parameter. Thanks
Did you mean estimator instead of parameter? Outside of bayesian statistics, parameters do not normally have a variance.
True Value: Y
You may find it interesting to note that the quatratic ("B") factorises to give
So that for an unbiased estimator, the MSE is equal to the variance of the estimate (as you'd expect from the definition of a variance).