Timeline for linear regression independence issue
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 30, 2019 at 15:50 | comment | added | mlofton | Okay. So, if it's non-random, then there's no variance ( much less any covariance ) and the OP's issue is hopefully straightened out now. | |
| Oct 29, 2019 at 18:24 | history | edited | Jesper for President | CC BY-SA 4.0 |
deleted 68 characters in body
|
| Oct 29, 2019 at 9:29 | comment | added | Jesper for President | Yes $x_0$ is treated as non-random. | |
| Oct 29, 2019 at 9:23 | history | edited | Jesper for President | CC BY-SA 4.0 |
deleted 3 characters in body
|
| Oct 29, 2019 at 9:04 | history | edited | Jesper for President | CC BY-SA 4.0 |
added 1 character in body
|
| Oct 29, 2019 at 7:56 | history | edited | Jesper for President | CC BY-SA 4.0 |
added 57 characters in body
|
| Oct 29, 2019 at 5:31 | comment | added | mlofton | But I think that study_meow is saying ( albeit in a slightly different way): "How can be $\hat\beta$ and $\beta$ be independent since $\hat\beta$ is the estimate of $\beta$ !!!!!. To me, it's a great question and not intuitive. I think the best way to think about it is to NOT THINK of $x_{0}^{\prime} \beta$ as a random variable. Think of it as a constant which therefore is not a random variable. But that's just me. I'm not sure what the correct interpretation is. | |
| Oct 29, 2019 at 3:47 | history | answered | Jesper for President | CC BY-SA 4.0 |