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