Timeline for Why do we define the standard error to ignore bias (unlike MSE which includes bias)?
Current License: CC BY-SA 4.0
4 events
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| Jan 6 at 1:21 | comment | added | SRobertJames | I agree that a properly constructed hypothesis test should use the p-value and take into account bias, but the standard formulas do not. They just the standard error of the estimator: see, for example, Wikipedia's formula for Wald test. | |
| Jan 5 at 23:27 | comment | added | Ben | You assert relevance for hypothesis testing, but that sounds wrong to me. A properly constructed hypothesis test uses the p-value for its outcome, which should take into account any relevant bias, etc. (assuming that the test statistic is even based on an estimator). It is unclear to me why you think that hypothesis testing would be adversely affected by the existing concept of standard error. | |
| Jan 5 at 23:04 | comment | added | SRobertJames | I can accept that names can be due to historical circumstances, not ideal, but not a problem in practice. But, in this case, it actually makes a difference to results of hypothesis testing. Can you please take a look at my update to the question? | |
| Jan 5 at 22:45 | history | answered | Ben | CC BY-SA 4.0 |