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BU.232.630.F3.SP25 sample quiz 1

ๅ•้กน้€‰ๆ‹ฉ้ข˜

Consider a population with mean ๐œ‡ and variance ๐œŽ 2 < โˆž . Assume the following two estimators ๐œ‡ ฬ‚ 1 and ๐œ‡ ฬ‚ 2 for the mean of the population ๐œ‡ , with the following expected values and variances ๐ธ ( ๐œ‡ ฬ‚ 1 ) = ๐œ‡ ; ๐‘‰ ( ๐œ‡ ฬ‚ 1 ) = 5 ; ๐ธ ( ๐œ‡ ฬ‚ 1 ) = ๐œ‡ + 1 ; ๐‘‰ ( ๐œ‡ ฬ‚ 2 ) = 2 . We also know that the covariance between the two estimators is ๐ถ ๐‘‚ ๐‘‰ ( ๐œ‡ ฬ‚ 1 , ๐œ‡ ฬ‚ 2 ) = โˆ’ 1 . Now consider a new estimator that combines the two previous ones ๐œ‡ ฬ‚ 3 = 1 3 ๐œ‡ ฬ‚ 1 + 2 3 ๐œ‡ ฬ‚ 2 . Then the variance ๐‘‰ ( ๐œ‡ ฬ‚ 3 ) of ๐œ‡ ฬ‚ 3 is

้€‰้กน
A.2.5556
B.3
C.1
D.๐œŽ 2 + 1.4444
E.1.4444
F.๐œŽ 2 -1
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To determine the variance of the combined estimator mu_hat_3, we use the linear combination formula for variances with covariance: Var(aX + bY) = a^2 Var(X) + b^2 Var(Y) + 2ab Cov(X,Y). First, identify the coefficients from mu_hat_3 = (1/3) mu_hat_1 + (2/3) mu_hat_2. Here a = 1/3 and b = 2/3. Next, plug in the given......Login to view full explanation

็™ปๅฝ•ๅณๅฏๆŸฅ็œ‹ๅฎŒๆ•ด็ญ”ๆกˆ

ๆˆ‘ไปฌๆ”ถๅฝ•ไบ†ๅ…จ็ƒ่ถ…50000้“่€ƒ่ฏ•ๅŽŸ้ข˜ไธŽ่ฏฆ็ป†่งฃๆž,็Žฐๅœจ็™ปๅฝ•,็ซ‹ๅณ่Žทๅพ—็ญ”ๆกˆใ€‚

็ฑปไผผ้—ฎ้ข˜

Consider a population with mean ฮผ and variance ฯƒ2<โˆž. You are comparing two estimators ห† ฮผ 1 and ห† ฮผ 2 for the mean of the population ฮผ, with the following expected values and variances E( ห† ฮผ 1)=ฮผ;V( ห† ฮผ 1)=9; E( ห† ฮผ 1)=ฮผ+1;V( ห† ฮผ 2)=1. We also know that the covariance between the two estimators is COV( ห† ฮผ 1, ห† ฮผ 2)=โˆ’2. Now consider a new estimator that combines the two previous ones ห† ฮผ 3= 1 3 ห† ฮผ 1+ 2 3 ห† ฮผ 2. Then the variance V( ห† ฮผ 3) of ห† ฮผ 3 is

Consider a population with mean ๐œ‡ and variance ๐œŽ 2 < โˆž . Assume the following two estimators ๐œ‡ ฬ‚ 1 and ๐œ‡ ฬ‚ 2 for the mean of the population ๐œ‡ , with the following expected values and variances ๐ธ ( ๐œ‡ ฬ‚ 1 ) = ๐œ‡ ; ๐‘‰ ( ๐œ‡ ฬ‚ 1 ) = 5 ; ๐ธ ( ๐œ‡ ฬ‚ 1 ) = ๐œ‡ + 1 ; ๐‘‰ ( ๐œ‡ ฬ‚ 2 ) = 2 . We also know that the covariance between the two estimators is ๐ถ ๐‘‚ ๐‘‰ ( ๐œ‡ ฬ‚ 1 , ๐œ‡ ฬ‚ 2 ) = โˆ’ 1 . Now consider a new estimator that combines the two previous ones ๐œ‡ ฬ‚ 3 = 1 3 ๐œ‡ ฬ‚ 1 + 2 3 ๐œ‡ ฬ‚ 2 . Then the variance ๐‘‰ ( ๐œ‡ ฬ‚ 3 ) of ๐œ‡ ฬ‚ 3 is

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