Timeline for How can I test the likelihood that two Poisson data sets are drawn from the same distribution in R?
Current License: CC BY-SA 3.0
7 events
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| Mar 3, 2013 at 18:30 | comment | added | whuber♦ | (BTW, the purpose in suggesting a regression is that it makes it easy to adjust for any covariates. In this application there ought to be some: certainly time; and probably type of code, programmer identifier, and other relevant attributes as well.) | |
| Mar 3, 2013 at 17:54 | vote | accept | Xodarap | ||
| Mar 3, 2013 at 2:39 | answer | added | Glen_b | timeline score: 3 | |
| Mar 2, 2013 at 23:26 | comment | added | whuber♦ | A "significant" dummy for a binary independent variable means there is evidence that the mean values of the response vary with the level of the binary variable. That sounds exactly like the hypothesis you wish to test. A simple adjustment will turn the default two-sided test into a one-sided test if you like. | |
| Mar 2, 2013 at 23:23 | comment | added | Xodarap |
@whuber: To be honest, I was never sure what it meant to say that a variable was "significant". You're saying that "weekends is significant at p = a" means "the likelihood that both distributions are drawn from a distribution unaffected by weekends is a"?
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| Mar 2, 2013 at 23:17 | comment | added | whuber♦ | Why run two regressions when you can run one with a dummy variable for weekends and just test its significance? | |
| Mar 2, 2013 at 23:13 | history | asked | Xodarap | CC BY-SA 3.0 |