Timeline for How to understand this coefficient in a linear regression confidence interval?
Current License: CC BY-SA 4.0
12 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 5, 2023 at 23:51 | vote | accept | Basj | ||
| S Nov 5, 2023 at 23:07 | history | bounty ended | CommunityBot | ||
| S Nov 5, 2023 at 23:07 | history | notice removed | CommunityBot | ||
| S Oct 28, 2023 at 21:21 | history | bounty started | Basj | ||
| S Oct 28, 2023 at 21:21 | history | notice added | Basj | Canonical answer required | |
| Oct 17, 2023 at 17:27 | comment | added | Lukas Lohse | @DemetriPananos I don't see the inclusion of residual variance. I think this is just std. error. It's easier to see when you take $x_0 = \bar{x}$, where you get $S\sqrt{1/n}$ | |
| Oct 17, 2023 at 17:24 | answer | added | Lukas Lohse | timeline score: 2 | |
| Oct 17, 2023 at 17:23 | comment | added | Demetri Pananos | Excuse me, this should be the combined uncertainty. The two sources of uncertainty are uncertainty in the outcome (i.e. the noise) and uncertainty in the mean. When the appropriate t statistic is applied, this can result in a prediction interval. | |
| Oct 17, 2023 at 16:48 | comment | added | Basj | @DemetriPananos Thank you. Just to be sure, then, why is $t_{1−α/2;n−2}$ absent of $c$ ? | |
| Oct 17, 2023 at 16:19 | comment | added | Demetri Pananos | This quantity appears to be the prediction interval when the predictor, $x0$ is 0. | |
| Oct 17, 2023 at 16:01 | history | edited | Basj | CC BY-SA 4.0 |
edited body; edited title
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| Oct 17, 2023 at 15:30 | history | asked | Basj | CC BY-SA 4.0 |