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Mean Square Error (MSE) of estimator decomposes as:
AStandard error
BJust variance
CMSE = Variance + Bias² (basic bias-variance decomposition)
DBias
Answer & Solution
Correct answer: C. MSE = Variance + Bias² (basic bias-variance decomposition)
MSE = E[(θ̂ - θ)²] = Var(θ̂) + (E(θ̂) - θ)² = Var + Bias². Foundation of estimator comparison. Trade-off: low-bias estimators often have high variance.
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