Timeline for Spot a bad linear regression fit from model output?
Current License: CC BY-SA 3.0
8 events
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| Feb 10, 2019 at 5:01 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Mar 7, 2016 at 14:03 | comment | added | Glen_b | You cannot tell from that output whether the model is suitable or not. See the four data sets in the Anscombe quartet which have identical output. | |
| Mar 7, 2016 at 12:28 | answer | added | Christoph Hanck | timeline score: 1 | |
| Mar 7, 2016 at 12:23 | comment | added | Nick Cox | Nothing in the usual output tells you anything about causal relationships. Causality is all in the design and substantive context and interpretation. | |
| Mar 7, 2016 at 12:16 | comment | added | Greenparker | There is the usual $R^2$ value which indicates how good the linear fit is. This will be a function of the estimated variance, so that might give a good idea. | |
| Mar 7, 2016 at 12:14 | history | edited | gung - Reinstate Monica | CC BY-SA 3.0 |
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| Mar 7, 2016 at 12:12 | review | First posts | |||
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| Mar 7, 2016 at 12:12 | history | asked | Januman | CC BY-SA 3.0 |