Let X1 be the sample mean of a random sample of size n from a Normal(µ, o7) population and X2 be the sample mcan of a random sample of the same size n from a Normal(4, o) population and the two samples are independent. Note that the two samples have the same population Imean ți but o o. Let i = wX1 +(1 – w)X2,0

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Let X1 be the sample ncan of a random sanple of size n from a Norimal(µ, of) population and
X2 be the sample mean of a random sample of the same size n from a Normal(4, o,) population
and the two samples are independent. Note that the two samples have the same population
mcan ji but oio.
TL
Let ji = wX1 +(1 – w)X2,0<w<1 be an cstimator for ji. Is îî unbiased for
? Explain.
Find the valuc of w in [0,1] so that Var(î) is minimized. Hint: take the
derivative of Var(ſî) with respect to w and set it equal to 0.
Let ji' := w' X|+(1-w*)X2 where w' is the answer from part b. If we assume
that all population parameters µ,07,0% are unknown, does it make sense to use i* as an
estimator for µ? If ycs, explain why. If no, provide a modification of i* that has a similar
structure but makes sense as an estimator for u.
Transcribed Image Text:Let X1 be the sample ncan of a random sanple of size n from a Norimal(µ, of) population and X2 be the sample mean of a random sample of the same size n from a Normal(4, o,) population and the two samples are independent. Note that the two samples have the same population mcan ji but oio. TL Let ji = wX1 +(1 – w)X2,0<w<1 be an cstimator for ji. Is îî unbiased for ? Explain. Find the valuc of w in [0,1] so that Var(î) is minimized. Hint: take the derivative of Var(ſî) with respect to w and set it equal to 0. Let ji' := w' X|+(1-w*)X2 where w' is the answer from part b. If we assume that all population parameters µ,07,0% are unknown, does it make sense to use i* as an estimator for µ? If ycs, explain why. If no, provide a modification of i* that has a similar structure but makes sense as an estimator for u.
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