Hello,
I am reasoning about a question concerning the t-test for one sample. My
data includes 150 values (mean 10.07) which I want to compare to mu=9. A
tow-sided t-test yields
> t.test(data,mu=9)
One Sample t-test
data: data
t = 3.0099, df = 149, p-value = 0.00307
alternative hypothesis: true mean is not equal to 9
95 percent confidence interval:
9.368676 10.777991
sample estimates:
mean of x
10.07333
The result would be interpreted as being significant. Furthermore it can
be said that the true mean is greater than 9 because of the confidence
interval.
*My question is*: Why does it seem to be not possible to conduct a
t-test with option "greater"? The result I get is:
> t.test(data,"greater",mu=9)
Fehler in t.test.default(data, "greater", mu = 9) :
nicht genug 'y' Beobachtungen
R complains about the amount of supplied data.
I'd like to understand this behavior.
Thank you for any hints!
Karsten
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
