Timeline for Changes in the regression coefficient
Current License: CC BY-SA 2.5
7 events
| when toggle format | what | by | license | comment | |
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| Mar 1, 2011 at 17:43 | comment | added | whuber♦ | Mighty nice work from a telephone interface! | |
| Mar 1, 2011 at 17:18 | comment | added | mpiktas | @whuber, you raised an interesting point. I've updated my question, but I'll need to check it. Unfortunately I am posting now via my phone, which rather limits my editing capabilities, so if I'll have something substantial to add it will be later. | |
| Mar 1, 2011 at 17:15 | history | edited | mpiktas | CC BY-SA 2.5 |
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| Mar 1, 2011 at 17:08 | comment | added | mpiktas | @whuber, I had the formula in wikipedia page in mind. There the difference between estimate of the regression coefficient and its true value is expressed as sum of two terms. The bias is expectation of this sum. The expectation of one term is always zero, since it involves the regression error. The expectation of another term is zero if there is no correlation between the omitted variables and the variables in the regression. I modified the answer to reflect your comment. | |
| Mar 1, 2011 at 17:01 | history | edited | mpiktas | CC BY-SA 2.5 |
added 28 characters in body
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| Mar 1, 2011 at 16:54 | comment | added | whuber♦ | It would be helpful to distinguish variables from the actual data. Even if the expected bias is zero, the actual bias is likely to be nonzero. In other words, the problem (as stated) seems to be about a dataset and not about an underlying model for the data by means of random variables, so the mention of expectation is a bit of a surprise. | |
| Mar 1, 2011 at 14:55 | history | answered | mpiktas | CC BY-SA 2.5 |