Re: Student's t vs. z tests

[Paul Swank]

They are more than just related. One is a natural extension of the other just as chi-square is a natural extension of Z. With linear models, one can begin with a simple one sample model and build up to multiple factors and covariates using the same basic framework, which I find easier to make sense of logically and easier to teach.

At 01:58 AM 4/19/01 -0300, you wrote:
>
>
>Paul Swank wrote:
>>
>> However, rather than do that why not right on to F? Why do t at all when you can do anything with F that t can do plus a whole lot more?
>
> Because the mean, normalized using the hypothesized mean and the
>observed standard deviation, has a t distribution and not an F
>distribution. I am aware that the two are algebraically related,(and
>simply) but trying to get through statistics with only one table (or
>only one menu item on your stats software) seems pointless - like trying
>to do all your logic with NAND operations just because you can.
>
> -Robert Dawson
>
------------------------------------
Paul R. Swank, PhD.
Professor & Advanced Quantitative Methodologist
UT-Houston School of Nursing
Center for Nursing Research
Phone (713)500-2031
Fax (713) 500-2033
soon to be moving to the Department of Pediatrics
UT Houston School of Medicine

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