Hello,
I'm not quite sure I understand, but something like this?
tapply(dat$Score, dat$Name, FUN = mean)
sapply(unique(dat$Name), function(un){
with(dat, t.test(Score[Name == un], Score[Name != un])$p.value)})
My doubt is in what you mean by "mean for CTK and all". The ?t.test
gives a confidence interval for the difference in the means, so maybe
you'll have to look there for what you want.
Hope this helps,
Rui Barradas
Em 04-10-2012 10:34, Nico Met escreveu:
Dear Group,
I want to do a t-test calculation on a large data set.
I am pasting some part of it
structure(list(Name = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L), .Label = c("CTK100", "CTK103", "CTK121"), class = "factor"),
Score = c(236.9726, 207.0055, 237.3464, 224.4774, 236.5034,
206.7382, 233.94, 240.31, 240.9, 235.15, 223.36, 248.67,
249.25, 201.4051, 244.1689, 182.2756, 229.001, 241.3211,
196.0453, 232.6055, 225.0783, 196.0453, 232.6055, 225.0783
)), .Names = c("Name", "Score"), class = "data.frame", row.names =
c(NA,
24L))
I want to compare groups with CTK100 and with all the groups and want to
save the p-values and mean for each of that particular group (for example:
mean for CTK and all)
Similarly, for other groups like that CTK121 etc...
Is there any way to automate this process?
Thanks for your advice !!!!!
Nico
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