Question: In simple linear regression, the i-th prediction is denoted as yi = Bo + BIT;, let bo = Bo = bo, b1 = B1, we

In simple linear regression, the i-th prediction is denoted as yi = Bo + BIT;, let bo = Bo = bo, b1 = B1, we also have: b1=r-, bo = y - bix SI where r is the correlation between x and y, and sy and s, are the standard deviation for x and y, respectively. (a) [5 pts] Sum of Residuals: The i-th residual from ordinaary least squares is defined as the difference between the observed data and the predicition, i.e. e; = y; - 9. What is _ _je;? (Show details about how to get this value) (b) [5 pts] Sum of Fitted Values: show the sum of the observed value yi equals the sum of the fitted values gi. That is, Ellyi = El gi

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