Is this biased or unbiased Method of Moments Estimator?

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SUMMARY

The discussion centers on the unbiasedness of the Method of Moments Estimator (MME) for the parameter θ, derived from the sample mean and sample variance. The key equations presented include \(E(X) = \bar{X}\) and \(\theta = \frac{1}{n} \sum_{i=1}^{n} X_{i}^{2}\), confirming that the MME is indeed an unbiased estimator. The notation clarification emphasizes that \(\hat{\theta} = \frac{1}{n} \sum_{i=1}^{n} X_i^2\) should be used to avoid confusion. The final conclusion is that \(E(\hat{\theta}) = \bar{X^2} = \theta\), validating the unbiased nature of the estimator.

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songoku
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Homework Statement
Please see below
Relevant Equations
Method of Moments Estimator (MME)
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(i)
$$E(X)=\bar X$$
$$(-1)\left(\frac{\theta}{2}\right)+(1)\left(\frac{\theta}{2}\right)=\bar X$$
$$\bar X=0$$

Then:
$$\text{Var} (X)=\bar {X^2}-(\bar X)^2$$
$$(1)\left(\frac{\theta}{2}\right)+(1)\left(\frac{\theta}{2}\right)=\bar {X^2} - 0$$
$$\theta = \frac{1}{n} \sum_{i=1}^{n} X_{i}^{2}$$

(ii)
$$E(\hat {\theta})=E(\bar {X^2})=\theta$$

So the MME is unbiased estimator.

Is my working correct? Thanks
 
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(i) Your work is correct, but your notation should be clearer.
songoku said:
$$\theta = \frac{1}{n} \sum_{i=1}^{n} X_{i}^{2}$$
should be $$ \hat{\theta}=\frac1n\sum_{i=1}^{n}X_i^2 $$.
(ii) I do not understand how you get this
songoku said:
$$E(\hat {\theta})=E(\bar {X^2})=\theta$$
.
By following steps
$$ E(\hat{\theta})=E(\frac1n\sum_{i=1}^{n}X_i^2)=\frac1nE(\sum_{i=1}^{n}X_i^2)=... $$
you should get this $$ E(\hat{\theta})=\bar{X^2}=\theta $$ at the end.
 
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I understand.

Thank you very much Gavran
 
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