Ted this was very helpful. To be crystal clear I'll rephrase you.
What I am interested in is the probability that my 'T' is in the tail. For a two sided test I do not care which tail. Since (all things being equal) the distribution of T is around 0 if the my T is greater than 0 I compare it to the upper tail, and if it is less than 0 I compare it to the lower tail. 'pt' that gives the probability for one tail. I must be careful to choose the correct tail, and multiply by 2. Thank you again, Ted and everybody else who helped. As an aside this is why I wish I had done more statistical *theory* rather than applied statistics, of which I have done quite a bit. I do not know if it is just me, but it is me, theoretical underpinnings for this stuff is *very* important. This is a very simple concept and I spent a whole day (with the invaluable help of this list) trying to get my head around what I would have seen straight away with a better education. I cannot express my wonder and appreciation for the R community, its patience and perseverance. It is a truly marvellous thing. Worik Stanton Dunedin New Zealand On Fri, Jun 18, 2010 at 12:43 AM, Ted Harding <ted.hard...@manchester.ac.uk>wrote: > On 16-Jun-10 22:30:39, Worik R wrote: > > I have two pairs of related vectors > > x1,y1 > > and > > x2,y2 > > > > I wish to do a test for differences in means of x1 and y1, > > ditto x2 and y2. > > > > I am getting odd results. I am not sure I am using 'pt' properly... > > I have not included the raw vectors as they are long. > > I am interested if I am using R properly... > > > >> c(length(x1), length(y1), length(x2), length(y2)) > > [1] 3436 1619 2677 2378 > > > > First where the T-stat and the DF do not give the same result as > > 't.test' when passed into 'pt' > > > >> t.1 <- t.test(x1, y1) > >> 2 * pt(t.1$statistic, t.1$parameter) > > t > > 1.353946 > >> t.1$p.value > > [1] 0.646054 > > > > I would have thought these would have been the same. Like below.... > > > >> t.2 <- t.test(x2, y2) > >> 2 * pt(t.2$statistic, t.2$parameter) > > t > > 0.8679732 > >> t.2$p.value > > [1] 0.8679732 > > > > This is what I expect. > > > > clearly I misunderstand some thing. What is it? > > > > cheers > > Worik > > The P-value is the tail-area (or the sum of the two tail-areas > for a two-sided test). The value of pt() is the total probability > to the left of the upper tail. Taking your results above: > > [1]: > t.1 <- t.test(x1, y1) > 2 * pt(t.1$statistic, t.1$parameter) > # t > # 1.353946 > t.1$p.value > # [1] 0.646054 > > The "t.1$p.value" result will (by default) be the two-tailed test, > so one tail will have probability equal to half the P-value, > while the value of pt() will be Prob(T <= t1$statistic). > Hence the former will be 2*(1 - the latter) **provided the t-statistic > is positive** -- otherwise, if the t-statistic is negative, the > former is twice the latter. > > . Check: > > 2*(1 - 1.353946/2) > # [1] 0.646054 > > 2*(1 - 0.646054/2) > # [1] 1.353946 > > So this indicates that the t-value (which you did not quote) was > positive. > > [2]: > t.2 <- t.test(x2, y2) > 2 * pt(t.2$statistic, t.2$parameter) > # t > # 0.8679732 > t.2$p.value > # [1] 0.8679732 > > 2*(1 - 0.8679732/2) > # [1] 1.132027 > > (so no agreement), but: > > 2*(0.8679732/2) > # 0.8679732 > > so here the t-value was negative. And that is the difference between > thw two cases. > > Ted. > > -------------------------------------------------------------------- > E-Mail: (Ted Harding) <ted.hard...@manchester.ac.uk> > Fax-to-email: +44 (0)870 094 0861 > Date: 17-Jun-10 Time: 13:43:37 > ------------------------------ XFMail ------------------------------ > [[alternative HTML version deleted]] ______________________________________________ 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.