Timeline for Paired t-test assumptions
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 5, 2019 at 12:51 | vote | accept | Jose Ramon | ||
| Jul 3, 2019 at 12:34 | comment | added | Dave | @JoseRamon Both populations should have the same variance. The Welch test, which is the default "t-test" in R software, accounts for unequal variance. | |
| Jul 3, 2019 at 8:56 | comment | added | Jose Ramon | Then what exactly the constant variance means in that case. Should both population have similar variance? | |
| Jul 2, 2019 at 16:43 | comment | added | Dave | As I suspected, you're not doing a paired test. A paired test would be something like evaluating the performance on a test of Brad, Ronald, and John before starting their master's degrees and then again after. You're doing two-sample testing. Yes, if you want to use the t-test, you should examine your data to make sure the assumptions are met. (Some have said that it's improper to examine your data, since that examination could be wrong, though relying on prior knowledge or intuition instead of examining the data doesn't seem practical.) | |
| Jul 2, 2019 at 15:56 | comment | added | Jose Ramon | My scenario is that I have two population performing a test, for example, a bachelor and master students playing a game and I want to figure out whether their time and performance is significantly different. When I perform t-test it shows that their mean is significantly different but I guess also I need to have some assumptions like the one I mentioned before I am to perform the tests. | |
| Jul 2, 2019 at 13:42 | history | answered | Dave | CC BY-SA 4.0 |