Timeline for Multiple Linear Regression and Correlation of two beta estimates
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 22, 2021 at 8:46 | comment | added | wiwh | Look at the dimension of the matrix $X$: it is $4\times 4$. This is because $X$ is a $15\times 4$ matrix. The confusion comes from the fact that while you have only 3 variables $x_1, x_2, x_3$, you also have a constant in the first column, associated with the coefficient $\beta_0$. So all the indices are shifted by 1.... for instance the variance of $\beta_1$ appears in $\text{cov}(\hat\beta)_{2,2}$. | |
| Nov 21, 2021 at 23:29 | comment | added | compscinewb | Can you explain how you know which index in the matrix to look at? | |
| Nov 21, 2021 at 18:02 | comment | added | whuber♦ | +1 Note, though, that the references to $s^2$ are only distracting from the ideas because the scale factor $s$ does not affect any correlations and can be ignored. | |
| Nov 21, 2021 at 17:49 | history | answered | wiwh | CC BY-SA 4.0 |