Timeline for How to understand t-value in R's lm()?
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 10, 2015 at 8:08 | vote | accept | HappyCoding | ||
| Nov 9, 2015 at 2:13 | comment | added | HappyCoding | thanks. for comments are very helpful. I just highlighted here Note that the standard error of the mean is s/sqrt(n), where s is the standard deviation of the data. | |
| Nov 9, 2015 at 1:55 | comment | added | HappyCoding | thanks @Glen_b! That's great! It could be even better if you can also explain a bit on the differences and connections between t-statistic in sampling and regression, besides the formula difference as you pointed out above. | |
| Nov 9, 2015 at 1:53 | history | edited | Glen_b | CC BY-SA 3.0 |
deleted 33 characters in body
|
| Nov 9, 2015 at 1:52 | comment | added | Glen_b | @HappyCoding Thanks for the heads up; I'll edit my answer a tiny bit; that should make things clearer for later readers (because there's fewer sources of confusion, the central issue about the standard error is clearer) | |
| Nov 9, 2015 at 1:48 | comment | added | HappyCoding | thanks @Glen_b for pointing out t distribution is different from t-statistic in regression. follow yours suggestion, I did some search and read in stattrek.com/regression/slope-test.aspx?Tutorial=AP. it's much clearer now. | |
| Nov 8, 2015 at 15:58 | history | edited | Glen_b | CC BY-SA 3.0 |
added 68 characters in body
|
| Nov 8, 2015 at 15:53 | history | answered | Glen_b | CC BY-SA 3.0 |