4. In this question, we are going to test the bias and efficiency of estimators. For this question assume that X follows an unknown distribution; however, we do know that E[X] = µ and Var[X] = 0² Moreover, we are able to somehow sample n i.i.d. data from the population X. Let's denote our sample as {X₁, X2, Xn} 2 Let's focus on the mean, . = ΣΧ. So far, our best estimate of our sample is the sample mean X Nevertheless, you may wake up one day and think "why should we compute the sample mean every time? It feels so tedious." You have decided to rather use the following estimator: ê = 2X1 + X2 + X3 + ... + Xn n+1 n (a) Calculate the bias of this estimator to respect to the population mean. Show all steps in the calculation. (b) Is this estimator unbiased for u? (c) Calculate variance of this estimator. Show your work. (d) Assume n > 1. Compare the efficiency of ô and X. Which one would you choose as an estimator for the population mean?

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4. In this question, we are going to test the bias and efficiency of estimators.
For this question assume that X follows an unknown distribution; however,
we do know that E[X] μ and Var[X] = 0²
=
Moreover, we are able to somehow sample n i.i.d. data from the population
X. Let's denote our sample as {X₁, X2,,Xn}
Let's focus on the mean, ul.
n
So far, our best estimate of our sample is the sample mean X = ½ Σï_₁ X₁.
Nevertheless, you may wake up one day and think "why should we compute the
sample mean every time? It feels so tedious."
You have decided to rather use the following estimator:
2X₁ + X2 + X3 + + Xn
n+1
Ô
(a) Calculate the bias of this estimator to respect to the population mean.
Show all steps in the calculation.
(b) Is this estimator unbiased for μ?
(c) Calculate variance of this estimator. Show your work.
(d) Assume n > 1. Compare the efficiency of ô and X. Which one would
you choose as an estimator for the population mean?
Transcribed Image Text:4. In this question, we are going to test the bias and efficiency of estimators. For this question assume that X follows an unknown distribution; however, we do know that E[X] μ and Var[X] = 0² = Moreover, we are able to somehow sample n i.i.d. data from the population X. Let's denote our sample as {X₁, X2,,Xn} Let's focus on the mean, ul. n So far, our best estimate of our sample is the sample mean X = ½ Σï_₁ X₁. Nevertheless, you may wake up one day and think "why should we compute the sample mean every time? It feels so tedious." You have decided to rather use the following estimator: 2X₁ + X2 + X3 + + Xn n+1 Ô (a) Calculate the bias of this estimator to respect to the population mean. Show all steps in the calculation. (b) Is this estimator unbiased for μ? (c) Calculate variance of this estimator. Show your work. (d) Assume n > 1. Compare the efficiency of ô and X. Which one would you choose as an estimator for the population mean?
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