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  1. #1
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    Question Last one

    How do I prove that the variance of alpha in the equation:
    y hat= alpha hat+beta hat*x(i)
    is:
    MSE(1/n+(x bar^2/sum of (x(i)-xbar)^2))
    Assuming this is normal how would i got about actually proving that this is the variance?? Do I need to start with the expected value of y(i) and manipulate it?
    (MSE is the estimator of sigma^2)
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  2. #2
    Grand Panjandrum
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    Quote Originally Posted by Jar23 View Post
    How do I prove that the variance of alpha in the equation:
    y hat= alpha hat+beta hat*x(i)
    is:
    MSE(1/n+(x bar^2/sum of (x(i)-xbar)^2))
    Assuming this is normal how would i got about actually proving that this is the variance?? Do I need to start with the expected value of y(i) and manipulate it?
    (MSE is the estimator of sigma^2)
    Write down the equation for \hat{\alpha} then calculate the variance.

    RonL
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