Timeline for Testing the likelihood that two percentages are equal
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 8, 2011 at 11:24 | comment | added | Wolfgang | Your "leaning towards no" is correct. 1-p will be the probability of the observed data or less extreme data under the assumption of the null hypothesis. Again, that is different than the probability that the two percentages are the same. | |
| Sep 8, 2011 at 5:14 | vote | accept | JudoWill | ||
| Sep 8, 2011 at 5:12 | comment | added | JudoWill | @Wolfgang ... I understand that the chi-squared tells me the likelihood of finding values being this different given the assumption that they from the same distribution. I was unclear (and leaning towards no) as to whether a 1-p could be used to say that they truly were from the same distribution. | |
| Sep 8, 2011 at 4:52 | answer | added | Michael Lew | timeline score: 4 | |
| Sep 8, 2011 at 0:45 | history | tweeted | twitter.com/#!/StackStats/status/111600906079977473 | ||
| Sep 8, 2011 at 0:19 | comment | added | suncoolsu | In science you can't prove anything. | |
| Sep 7, 2011 at 22:59 | comment | added | Wolfgang | The p-value from the chi-square test does not tell you the likelihood that they are different. The p-value tells you what the probability is of the observed difference in the percentages or an even more extreme difference under the assumption that there really is no difference in the true percentages. That is something very different than the probability that the true percentages are different. | |
| Sep 7, 2011 at 22:08 | history | asked | JudoWill | CC BY-SA 3.0 |