Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: RE: one-tailed tests


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: one-tailed tests
Date   Thu, 8 Jul 2010 15:01:04 +0100

I don't know why anyone would want to do any test if you can get a
confidence interval. After all, most of the best science should be
quantitative, and a confidence interval is a report on the measurement
scale of interest: it summarizes information, it indicates uncertainty
and it can be compared with your qualitative ideas on sign or direction
quite easily. If you think that something should be positive, or
increase, or whatever, you can see whether the c.i. lies the correct
side of zero, or whatever. In contrast, a yes-no test decision or even a
P-value is a more cryptic and problematic reduction of the data. 

Actually, I don't know why anyone would get a confidence interval if you
can put most or all of the data on a graph. After all, a good graph
shows the main features of the data and detailed departures from those
features, and it can give you ideas on what next to do. 

I have to estimate the extent to which Eric or Roger was talking tongue
in cheek, and you will have to do the same about this. 

Nick 
n.j.cox@durham.ac.uk 

Eric Uslaner

Bea Potter asked how to do one-tailed tests and Roger Newson responded:
"I don't know why anybody would want to do a 1-tailed test, except if
the 
distribution of the test statistic, under the null hypothesis, really IS
one-tailed." 

I don't understand why anyone would do a two-tailed test.  If you have a
theory, that theory is directional: The more A, the more B.  A
two-tailed test is completely inappropriate for this.  E.g., in studies
of voting behavior in political science, we usually posit that party
identification is the dominant force behind voter choice.  So if you are
a strong Democrat, you will vote Democratic.  A two-tailed test would
imply that a strong Republican would be equally likely as a strong
Democrat to vote Democratic.  This is plain silly.  If you don't have a
theoretical focus, you don't have a research design worth submitting
anywhere.  

So I don't understand why anyone does two-tailed tests and why Stata
(together with other statistical programs) report them as defaults.


*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index