Timeline for Test for statistical significance in performance variability
Current License: CC BY-SA 3.0
3 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 26, 2015 at 16:08 | history | edited | RDJ | CC BY-SA 3.0 |
[Edit removed during grace period]
|
| Jun 26, 2015 at 15:10 | comment | added | brumar | This is it. For an obscure reason, in R I have X-squared = 18.7953 and p-value = 0.0008621 with your data but this is not that far. I don't know what to say about confounders. The most important factor - I think - is that your agents are in the same conditions to be compared. To study how big is your problem, and if you can request another dataset, you may study how variable are the performances across time. For example ask long run data and plot % of success every 100 calls to get an idea about how variable success rate is for a common agent. | |
| Jun 26, 2015 at 14:30 | history | answered | RDJ | CC BY-SA 3.0 |