Felipe Carrillo wrote:
Hi Ted:
Thanks for your prompt reply and explanation.
That's what I was wondering, why would one need to test mu=0 ,which is the t.test default. But reading Peter Dalgaard's book and looking at some examples online, I saw t.test being used like that; t.test(datasetname) with no other arguments
Umm, in ISwR, I can see
t.test(bmi, mu=22.5)
t.test(bmi, mu=22.5)$p.value
t.test(daily.intake,mu=7725)
t.test(daily.intake,mu=7725)
t.test(expend~stature)
t.test(expend~stature, var.equal=T)
t.test(pre, post, paired=T)
t.test(pre, post) #WRONG!
t.test(log10(diameter)~glucose)
None of those are of the form t.test(mydata).
You might occasionally want to test for mu=0, for instance in
t.test(post-pre), which is just another way of doing the paired t test.
mu=0 is the default because zero is the only value that "sticks out" as
a potentially hypothesized value (in particular, it is stable to
scaling of the data).
If you see cases where mu is not specified and the default 0 is not
interesting as a null hypothesis, then maybe the author was not
interested the test at all (e.g. the confidence interval is still useful).
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
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