Is the Distribution of Unbiased Estimates the Same as the Statistic?

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SUMMARY

The discussion centers on the relationship between unbiased estimators and their distributions, specifically in the context of normal random variables. It is established that the distribution of an unbiased estimator, such as the sample mean, coincides with the distribution of the parameter it estimates. The example provided involves five independent and identically distributed normal random variables with a variance of 1 and an unknown mean. Additionally, it is confirmed that multiple unbiased estimators can exist for the same parameter, each with distinct distributions, highlighting the concept of Minimum Variance Unbiased Estimator (MVUE).

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  • Understanding of unbiased estimators in statistics
  • Familiarity with normal distribution properties
  • Knowledge of sample mean calculation
  • Concept of Minimum Variance Unbiased Estimator (MVUE)
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  • Research the properties of unbiased estimators in statistical inference
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Statisticians, data analysts, and students studying statistical estimation methods will benefit from this discussion, particularly those interested in the properties of unbiased estimators and their distributions.

yhp266
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Hi all, I've been confused about this for a while. Since it wasn't mentioned in class or my textbook, it probably reflects a fundamental lack of understanding :(


With any unbiased estimator, why is the distribution of the estimates also the distribution of the statistic?


Eg, suppose we have 5 independent and identically distributed normal random variables with variance 1 and mean (unknown parameter).

We observe some numbers say { 4, 5, -2 ,7 , 12}.

and we use sample mean as the estimator for mean. The sample mean is clearly normally distributed.

But why is this also the distribution for mean
 
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And is it possible to have 2 different unbiased estimators for the same parameter?

Wouldnt it not make sense to have multiple distributions of estimates for a particular parameter
 
Last edited:
1/I don't understand your first question.
2/Yes, many unbiased estimators for one parameter is possible. Let x1,x2,...,xn be a sample form N(mu,sigma). Then sample mean or any xi is unbiased for mu but the have different distributions. Look up what is ment by MVUE.
 

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