Stats proof - unbiasedness of b1

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SUMMARY

The discussion focuses on proving the unbiasedness of the estimator b1 in statistics, specifically through the equation sum(n)(I=1)(k(I))*(x(I)) = 1. The term k(I) is defined as (x(I)-x(bar))/(sum(n)(j=1)(x(j)-x(bar))^2). The user attempts to rearrange the equation to facilitate the proof but encounters difficulties in proceeding further. The solution can be simplified using the summation notation for x_i and x_i^2, which leads to a more straightforward proof.

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bloynoys
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We are to prove sum(n)(I=1)(k(I))*(x(I)) = 1

Where (k(I))= (x(I)-x(bar))/(sum(n)(j=1)(x(j)-x(bar))^2



Attempt at solution:

I rearranged it to equal:

(1/(sum(n)(j=1)(x(j)-x(bar))^2))*(sum(n)(I=1)(x(I)-x(bar))*x(I))

I don't really know how to proceed. Sorry for the formatting issues, I am on mobile currently.
 
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everything can be written in terms of \sum_i x_i and \sum_i x_i^2, the rest is straightforward
 

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