Timeline for Standard way of determining if you have enough data to reliably compute success probability
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 22, 2011 at 23:49 | comment | added | Michael Hardy | The manual entry for binom.test says it does an exact test, so that's not what I was talking about above. Just exactly what it does is not yet clear to me. | |
| Jun 22, 2011 at 14:42 | comment | added | Tim Harper | wouldn't want to use that data to impact my control chart or trigger an alert. (I'm writing a data monitoring system) | |
| Jun 22, 2011 at 14:41 | comment | added | Tim Harper | Hi Michael, Thank you for your thoughtful response. I'm using R function binom.test to compute the 95% confidence interval as I'm prototyping now, but am going to need to re-code my solution and will end up using the same formula you listed up above, thank you :) As far as the null hypothesis goes, I'm calculating the daily proportion of daily successes in a defined body of samples. I suppose the null hypothesis would be, in this instance, that there is not enough data to trust the calculation. If my average proportion was 0.1%, and on one day I had 0 leads of 500, I.... | |
| Jun 22, 2011 at 14:31 | vote | accept | Tim Harper | ||
| Jun 21, 2011 at 23:45 | history | answered | Michael Hardy | CC BY-SA 3.0 |