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BU.232.630.W4.SP25 sample_quiz_3

Single choice

Consider the likelihood of an i.i.d. sample from a Bernoulli population with parameter ๐‘ ๐ฟ ( ๐‘ฅ 1 , . . . , ๐‘ฅ ๐‘‡ ) = โˆ ๐‘ก = 1 ๐‘‡ ๐‘ ๐‘ฅ ๐‘ก ( 1 โˆ’ ๐‘ ) 1 โˆ’ ๐‘ฅ ๐‘ก . If you estimate the parameter ๐‘ using a Maximum Likelihood estimator, you obtain the point estimate ๐‘ ฬ‚ = 1 ๐‘‡ โˆ‘ ๐‘ก = 1 ๐‘‡ ๐‘ฅ ๐‘ก , which corresponds to the sample mean. We know that for a Bernoulli random variable the expected value and the variance are ๐”ผ ( ๐‘ฅ ๐‘ก ) = ๐‘ , ๐• ( ๐‘ฅ ๐‘ก ) = ๐‘ ( 1 โˆ’ ๐‘ ) . Using this information, what is the variance of the estimator ๐• ( ๐‘ ฬ‚ ) ?

Options
A.The variance of ๐‘ ฬ‚ is ๐• ( ๐‘ ฬ‚ ) = ๐‘ 2
B.The variance of ๐‘ ฬ‚ is ๐• ( ๐‘ ฬ‚ ) = ๐‘ ( 1 โˆ’ ๐‘ ) ๐‘‡
C.The variance of ๐‘ ฬ‚ is ๐• ( ๐‘ ฬ‚ ) = ๐‘ ( 1 โˆ’ ๐‘ )
D.The variance of ๐‘ ฬ‚ is ๐• ( ๐‘ ฬ‚ ) = ๐”ผ ( ๐‘ 2 )
E.All the answers are incorrect.
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Step-by-Step Analysis
We start by considering what we know about the Bernoulli(p) population and the estimator p-hat. The data x1, ..., xT are i.i.d. Bernoulli(p), and p-hat = (1/T) โˆ‘ xt is the sample mean. For a Bernoulli random variable, E[xt] = p and Var(xt) = p(1โˆ’p). Since p-hat is the average of T independent copies, its variance is Var(p-hat) = Var((1/T) โˆ‘ xt) = (1/T^2) โˆ‘ Var(xt) by independence, which simplifies to (1/T^2) ยท T ยท p(1โˆ’p) = p(1โˆ’p)/T. Now let's ......Login to view full explanation

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