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.