Mean squared error (MSE) is defined as the expected squared difference between the estimator and the true parameter. Which statement is true?

Mean squared error (MSE) is defined as the expected squared difference between the estimator and the true parameter. Which statement is true?

• A. It is a function of the true parameter.
• B. It is independent of the true parameter.
• C. It equals the estimator variance only.
• D. It equals the bias squared only.

Answer: (A)