The question is to fill out the missing numbers (A-L) of a simple linear regression model. I am having problems with converting and interpreting the given table in terms of variables. Would it be possible for someone to confirm and clarify things for me.
The first table represents regression statistics
True model $$ Y_t = \beta_o + \beta_1X_t + \mu_t $$
Estimated model $$ \hat Y_t = \hat\beta_0 + \hat\beta_1x_t $$
This is what I am confused about
- Does the first standard error ($12.8478$) mean $\sum\hat\mu_t^2$ ?
- Does the standard error for the intercept in last table ($14.6208$) mean $\sum\mu_t^2$ ?
- Does $3.8508$ equal $\hat\beta_1$ ?
- In order to calculate RSS (for J) I need $\sum \hat\mu_t^2$ does this confirm that my first two points are incorrect
- I know $G=\hat\beta_1^2\sum x_t^2$, how do I find $\sum x_t^2$
If I am wrong, would it be possible to know what those numbers mean in terms of variables