Timeline for Why compare sum of squares with ANOVA (and not mean)?
Current License: CC BY-SA 3.0
3 events
| when toggle format | what | by | license | comment | |
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| Jul 15, 2012 at 23:49 | comment | added | Joel W. | The mean squares are independent estimates of the population variance. The population variance being estimated is that for the whole population. Under the null hypothesis that there are no mean score differences due to treatments, these several variance estimates should be equal (or not significantly different). For example, if your estimate of the population variance based on the Ka factor A means is greater than your estimate of the population variance based on within group calculations, this difference can be evaluated by the F ratio. The F ratio is a ratio of two variance estimates. | |
| Jul 14, 2012 at 0:14 | comment | added | Michael R. Chernick | This is wrong. What population variance does it represent? | |
| Jul 13, 2012 at 12:50 | history | answered | Joel W. | CC BY-SA 3.0 |