Timeline for Uses and estimation of Student-t distribution
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 23, 2015 at 7:30 | comment | added | linksys | i suggest you give an example of this standardization you've seen other people do outside the context of calculating a t statistic. standardization can have uses other situations which i'm sure you can learn about by searching the internet or even this site, but i'm not aware of any that are specific to the situation where the population is t distributed. | |
| Dec 23, 2015 at 7:15 | comment | added | Celeste | Okay, to me then the Wikipedia page is misleading in that it doesn't sufficiently explain the more general use. In terms of the dof, that was obvious I missed that. I asked second question as I have notice some people standardising and un-standardising in a context that only makes sense in a t-test as you say, but I don't think is correct | |
| Dec 23, 2015 at 6:49 | comment | added | linksys | actually, the block quote starts mid-sentence after you began with "it is used"... that's not what the wikipedia page says... it says that the t-distribution "arises when estimating...", which i don't disagree with. moving on... if you have data from a t-distribution you can estimate the degrees of freedom by maximum likelihood, or you could notice from the wikipedia page that the variance is v=df/(df-2), which suggests estimating df as 2v/(v-1). your second question only seems to make sense in the context of the t-test and seems to have nothing to do with analyzing data that is t distributed. | |
| Dec 23, 2015 at 6:34 | comment | added | Celeste | The block quote is directly from Wikipedia and I have read the Wikipedia page, which I don't think answers my two questions: (1) how to estimate the DoF and (2) whether it is still required to divide the sample SD by the square root of n when standardising if one is not modelling the sample mean from a normal population | |
| Dec 23, 2015 at 6:14 | history | answered | linksys | CC BY-SA 3.0 |