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This is a practice problem. I've solved part (a). I have provided verified answers (from the published key) to all parts (a), (b) and & (c). I need help solving (b) and (c).

Consider a simple liner regression model of the form: Y = a + bX + error.
Given are the following summed information:

$\sum X = 383$
$\sum Y = 2495$
$\sum X^2 = 17443$
$\sum Y^2 = 757257$
$\sum (X*Y) = 114417$
and $n = 9$

(a) Find the regression equation of Y on X based on the above data.
(Answer: $Y$ = -29.178 + 7.20 * (X) + error)

(b) Calculate the estimated standard deviation of the regression equation error.
(Answer: 29.8454)

(c) Suppose the Durbin Watson statistic value for the regression is 1.5915. Then the approximate correlation between the residual and its first lag is given by?
(Answer: 0.2043)

Please help me understand how to solve part (b) and (c).


Thoughts:

I found the $R^2$ and Adjusted $R^2$ values from the SSE, SST, SSR calculations. The adjusted $R^2$ value is slightly lower (.89) than the $R^2$ value (.90).

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Your textbook did not define terms or give examples beforehand? –  J. M. Sep 11 '11 at 11:47
    
Not pertaining to what is asked here :( The reference I have is a bit advanced and disposes most of this stuff within the first few pages and moves on to advanced topics. –  IntelligentMoron Sep 11 '11 at 15:21

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