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ๅ้กน้ๆฉ้ข
Consider the likelihood of an i.i.d. sample from a Bernoulli population with parameter ๐ ๐ฟ ( ๐ฅ 1 , . . . , ๐ฅ ๐ ) = โ ๐ก = 1 ๐ ๐ ๐ฅ ๐ก ( 1 โ ๐ ) 1 โ ๐ฅ ๐ก . If you estimate the parameter ๐ using a Maximum Likelihood estimator, you obtain the point estimate ๐ ฬ = 1 ๐ โ ๐ก = 1 ๐ ๐ฅ ๐ก , which corresponds to the sample mean. We know that for a Bernoulli random variable the expected value and the variance are ๐ผ ( ๐ฅ ๐ก ) = ๐ , ๐ ( ๐ฅ ๐ก ) = ๐ ( 1 โ ๐ ) . Using this information, what is the variance of the estimator ๐ ( ๐ ฬ ) ?
้้กน
A.The variance of
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B.The variance of
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C.All the answers are incorrect.
D.The variance of
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E.The variance of
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Let's walk through each answer choice carefully and connect them to the underlying statistics of an i.i.d. Bernoulli sample.
Option 1: The variance of pฬ is V(pฬ) = p^2.
This is incorrect. The estimator pฬ = (1/T) โ x_t is the sample mean of Bernoulli( p ) draws. Each x_t has variance p(1โp). The variance of the average of T i.i.d. observations is the individual variance divided by T, not p^2. So V(pฬ) = p(......Login to view full explanation็ปๅฝๅณๅฏๆฅ็ๅฎๆด็ญๆก
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What's the variance of the average of n points ofย random variables X. All X's are independent and identically distributed. That is, what's V(), for i = 1 to n? ____________________________________________________ (reminder: )
What is the variance of a mean of a set of n independent and identically distributed random variables? V(xbar) | X ~ iid
What's the variance of the average of n points of X. All X's are independent and identically distributed. That is, what's V(xbar)?
What's the variance of the average of n points ofย random variables X. All X's are independent and identically distributed. That is, what's V( ยฏ X ), for i = 1 to n? ____________________________________________________ (reminder: )
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