Re: Student's t vs. z tests

[Paul Swank]

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?

At 10:58 PM 4/19/01 -0400, you wrote:
>students have enough problems with all the stuff in stat as it is ... but,
>when we start some discussion about sampling error of means ... for use in
>building a confidence interval and/or testing some hypothesis ... the first
>thing observant students will ask when you say to them ...
>
>assume SRS of n=50 and THAT WE KNOW THAT THE POPULATION SD = 4 ... is: if
>we are trying to do some inferencing about the population mean ... how come
>we know the population sd but NOT the mean too? most find this notion
>highly illogical ... but we and books trudge on ...
>
>and they are correct of course in the NON logic of this scenario
>
>thus, it makes a ton more sense to me to introduce at this point a t
>distribution ... this is NOT hard to do ... then get right on with the
>reality case ....
>
>asking something about the population mean when everything we have is an
>estimate ... makes sense ... and is the way to go
>
>in the moore and mccabe book ... the way they go is to use z first ...
>assume population is normal and we know sd ... spend alot of time on that
>... CI and logic of hypothesis testing ... THEN get into applications of t
>in the next chapter ...
>
>i think that the benefit of using z first ... then switching to reality ...
>is a misguided order
>
>finally, if one picks up a SRS random journal and looks at some SRS random
>article, the chance of finding a z interval or z test being done is close
>to 0 ... rather, in these situations, t intervals or t tests are almost
>always reported ...
>
>if that is the case ... why do we waste our time on z?
>
>
>
>At 08:52 PM 4/18/01 -0300, Robert J. MacG. Dawson wrote:
>>David J Firth wrote:
>> >
>> > : You're running into a historical artifact: in pre-computer days,
>> using the
>> > : normal distribution rather than the t distribution reduced the size
>> of the
>> > : tables you had to work with. Nowadays, a computer can compute a t
>> > : probability just as easily as a z probability, so unless you're in the
>> > : rare situation Karl mentioned, there's no reason not to use a t test.
>> >
>> > Yet the old ways are still actively taught, even when classroom
>> > instruction assumes the use of computers.
>>
>> The z test and interval do have some value as a pedagogical
>>scaffold with the better students who are intended to actually
>>_understand_ the t test at a mathematical level by the end of the
>>course.
>>
>> For the rest, we - like construction crews - have to be careful
>>about leaving scaffolding unattended where youngsters might play on it
>>in a dangerous fashion.
>>
>> One can also justify teaching advanced students about the Z test so
>>that they can read papers that are 50 years out of date. The fact that
>>some of those papers may have been written last year - or next- is,
>>however, unfortunate; and we should make it plain to *our* students that
>>this is a "deprecated feature included for reverse compatibility only".
>>
>> -Robert Dawson
>>
>>
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>_________________________________________________________
>dennis roberts, educational psychology, penn state university
>208 cedar, AC 8148632401, mailto:[EMAIL PROTECTED]
>http://roberts.ed.psu.edu/users/droberts/drober~1.htm
>
>
>
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------------------------------------
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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