Statistics Question - Expected value of an estimator

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The discussion revolves around the expected value of an estimator for the population mean, represented as \bar{Y}. It is established that the expected value of \bar{Y} equals the population mean, μ, because each component Y_i is a random sample from the population, which also has an expected value of μ. Participants clarify that the expected value of the estimator is derived from the fact that each sample Y_i shares the same statistical properties, including the mean. The conversation highlights the importance of understanding that the expected value of individual samples contributes to the overall expected value of the estimator. This foundational concept in statistics emphasizes the relationship between sample means and population means.
michonamona
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Hello friends!

Given an estimator of the population mean:

\bar{Y}=\frac{\sum^{N}_{i=1}Y_{i}}{N}

The expected value of \bar{Y} is :

E(\bar{Y}) = \frac{1}{N}E(Y_{1})+\frac{1}{N}E(Y_{2})+\cdots+\frac{1}{N}E(Y_{N})=\mu where \mu is the population mean.

Therefore:

E(\bar{Y}) = \frac{1}{N}\mu+\frac{1}{N}\mu+\cdots+\frac{1}{N}\mu


My question is, why are E(Y_{1}), E(Y_{2}), E(Y_{N}) all equal to \mu?
 
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michonamona said:
My question is, why are E(Y_{1}), E(Y_{2}), E(Y_{N}) all equal to \mu?

Isn't that exactly what is meant by "\mu is the population mean"?

By the way, you are missing a factor of 1/N in the definition of the estimator.
 
jbunniii said:
Isn't that exactly what is meant by "\mu is the population mean"?

By the way, you are missing a factor of 1/N in the definition of the estimator.

Thank you for your reply.

My mistake, I edited the equation.

But that's exactly what my question is about. If the Expected value of Ybar is equal to mu, then why is the expected value of EACH of the components of the series of Ybar also mu?

It must be something really simple that I'm missing...

Thanks
M
 
michonamona said:
Thank you for your reply.

My mistake, I edited the equation.

But that's exactly what my question is about. If the Expected value of Ybar is equal to mu, then why is the expected value of EACH of the components of the series of Ybar also mu?

It must be something really simple that I'm missing...

Thanks
M

Well, what ARE these components Y_i? I assume they are random samples from the population, are they not?

I think you are arguing in reverse. The expected value of the estimator is \mu BECAUSE the expected value of each of the random samples is \mu, not the other way around.
 
...expected value of each of the random samples is \mu, not the other way around.


so each of the random sample Y_i was taken from the population? meaning the size of each Y_i is the same as the population?


Thank you,
M
 
michonamona said:
so each of the random sample Y_i was taken from the population?

I don't know. I assume so, but you're the one who asked the original question. Is it homework? If so, doesn't the homework problem tell you what the Y_i's are?

meaning the size of each Y_i is the same as the population?

I don't know what you mean by "size." If each Y_i comes from the same population (more formally, the same probability distribution) then the STATISTICS should be the same for each Y_i. The mean (\mu) is one such statistic.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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