You might want to try using a non-parametric test, such as wilcox.test. How about some modification of the following:
d=data.frame(grp=rep(1:2,e=5),replicate(10,rnorm(100))); head(d) lapply(d[,-1],function(.column)wilcox.test(.column~grp,data=d)) David Freedman stephen sefick wrote: > > Up and down are the treatments. These are replicates within date for > percent cover of habiat. This is habitat data for a stream > restoration - up is the unrestored and dn is the restored. I have > looked at the density plots and they do not look gaussian - you are > absolutely right. Even log(n+1) transformed they do not look > Gaussian. Is there some other way that I would test for a difference > that you can think of? My thoughts were to run a Permutation t.test, > but I am very new to permutations, and don't know if this applies. > The other thing that I was thinking was to use a npmanova (adonis in > vegan) to test if the centroids of the habitat classifications were > different. I am in the process of working up my thesis data for > publication in a journal (there are other very interesting pieces to > the data set that I am working with, and this is one of the last > things that I need to wrap up before I can start editing/rewriting my > masters work). Any thoughts would be greatly appreciated. > thanks, > > Stephen Sefick > > 2009/5/16 Uwe Ligges <lig...@statistik.tu-dortmund.de>: >> >> >> stephen sefick wrote: >>> >>> I would like to preform a t.test to each of the measured variables >>> (sand.silt etc.) >> >> I am a big fan of applying t.test()s, but in this case: Are you really >> sure? >> The integers and particularly boxplot(x) do not indicate very well that >> the >> variables are somehow close to Gaussian ... >> >> >>> with a mean and sd for each of the treatments >> >> And what is the treatment??? >> >> Best, >> Uwe Ligges >> >> >>> (up or >>> down), and out put this as a table.... I am having a hard time >>> starting- maybe it is to close to lunch. Any suggestions would be >>> greatly appreciated. >>> >>> Stephen Sefick >>> >>> x <- (structure(list(sample. = structure(c(1L, 7L, 8L, 9L, 10L, 11L, >>> 12L, 13L, 14L, 2L, 3L, 4L, 5L, 6L, 1L, 7L, 8L, 9L, 10L, 11L, >>> 12L, 13L, 14L, 2L, 3L, 4L, 5L, 6L, 25L, 28L, 29L, 30L, 31L, 32L, >>> 33L, 34L, 35L, 26L, 25L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, >>> 26L, 27L, 25L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 26L, 15L, >>> 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 16L, 15L, 17L, 18L, 19L, >>> 20L, 21L, 22L, 23L, 24L, 16L, 36L, 39L, 40L, 41L, 42L, 43L, 44L, >>> 45L, 46L, 37L, 36L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 37L, >>> 38L), .Label = c("0805-r1", "0805-r10", "0805-r11", "0805-r12", >>> "0805-r13", "0805-r14", "0805-r2", "0805-r3", "0805-r4", "0805-r5", >>> "0805-r6", "0805-r7", "0805-r8", "0805-r9", "0805-u1", "0805-u10", >>> "0805-u2", "0805-u3", "0805-u4", "0805-u5", "0805-u6", "0805-u7", >>> "0805-u8", "0805-u9", "1005-r1", "1005-r10", "1005-r11", "1005-r2", >>> "1005-r3", "1005-r4", "1005-r5", "1005-r6", "1005-r7", "1005-r8", >>> "1005-r9", "1005-u1", "1005-u10", "1005-u11", "1005-u2", "1005-u3", >>> "1005-u4", "1005-u5", "1005-u6", "1005-u7", "1005-u8", "1005-u9" >>> ), class = "factor"), date = structure(c(2L, 2L, 2L, 2L, 2L, >>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = >>> c("10/1/05", >>> "8/29/05"), class = "factor"), Replicate = c(1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, >>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, >>> 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L >>> ), site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("dn", "up" >>> ), class = "factor"), sand.silt = c(20L, 45L, 90L, 21L, 80L, >>> 77L, 30L, 80L, 36L, 9L, 62L, 71L, 20L, 65L, 10L, 70L, 50L, 80L, >>> 90L, 97L, 94L, 82L, 30L, 10L, 65L, 80L, 90L, 70L, 10L, 50L, 60L, >>> 40L, 10L, 45L, 10L, 10L, 15L, 10L, 8L, 35L, 10L, 40L, 10L, 10L, >>> 28L, 5L, 45L, 35L, 2L, 10L, 40L, 2L, 70L, 40L, 20L, 30L, 50L, >>> 60L, 10L, 100L, 98L, 98L, 90L, 87L, 87L, 40L, 97L, 92L, 70L, >>> 50L, 81L, 35L, 70L, 89L, 28L, 28L, 82L, 81L, 33L, 80L, 40L, 40L, >>> 60L, 30L, 5L, 50L, 70L, 75L, 85L, 95L, 93L, 80L, 80L, 60L, 82L, >>> 60L, 5L, 70L, 80L, 40L), gravel = c(8L, 45L, 7L, 5L, 10L, 5L, >>> 35L, 7L, 45L, 60L, 0L, 0L, 5L, 8L, 25L, 0L, 45L, 15L, 0L, 1L, >>> 2L, 5L, 6L, 15L, 10L, 5L, 3L, 10L, 20L, 0L, 20L, 31L, 20L, 35L, >>> 70L, 30L, 60L, 60L, 70L, 50L, 70L, 40L, 50L, 30L, 48L, 85L, 20L, >>> 30L, 20L, 60L, 30L, 8L, 10L, 30L, 30L, 10L, 0L, 0L, 10L, 0L, >>> 0L, 0L, 2L, 8L, 8L, 30L, 0L, 3L, 15L, 29L, 11L, 60L, 15L, 8L, >>> 60L, 25L, 8L, 9L, 42L, 1L, 50L, 40L, 10L, 60L, 60L, 30L, 10L, >>> 10L, 0L, 0L, 0L, 2L, 2L, 0L, 1L, 25L, 10L, 10L, 10L, 50L), cobble = >>> c(5L, >>> 2L, 1L, 5L, 0L, 3L, 10L, 2L, 4L, 3L, 1L, 0L, 3L, 14L, 50L, 0L, >>> 1L, 1L, 0L, 0L, 0L, 2L, 0L, 5L, 0L, 0L, 2L, 5L, 3L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 30L, 5L, 2L, 1L, 0L, 0L, 0L, 5L, 35L, 3L, 0L, 0L, >>> 0L, 40L, 0L, 0L, 5L, 0L, 0L, 10L, 5L, 0L, 0L, 10L, 0L, 0L, 0L, >>> 0L, 1L, 1L, 30L, 0L, 0L, 0L, 10L, 4L, 3L, 2L, 0L, 2L, 0L, 0L, >>> 0L, 20L, 0L, 0L, 0L, 0L, 0L, 20L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 10L, 0L, 0L, 0L), boulder.bedrock = c(60L, 0L, >>> 0L, 45L, 0L, 0L, 0L, 0L, 0L, 8L, 10L, 0L, 35L, 5L, 8L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 10L, 60L, 70L, 0L, 0L, 0L, 5L, 55L, 0L, 0L, 0L, >>> 40L, 0L, 0L, 0L, 0L, 15L, 0L, 0L, 10L, 0L, 20L, 10L, 0L, 0L, >>> 0L, 0L, 20L, 0L, 0L, 60L, 0L, 0L, 20L, 0L, 10L, 0L, 50L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, 4L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 0L, 0L, 5L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 75L, 10L, 0L, 0L), fine.root = c(5L, 7L, >>> 0L, 10L, 2L, 6L, 5L, 4L, 3L, 7L, 0L, 0L, 7L, 4L, 6L, 1L, 4L, >>> 2L, 2L, 2L, 3L, 1L, 0L, 1L, 20L, 5L, 3L, 5L, 10L, 2L, 0L, 6L, >>> 10L, 10L, 15L, 0L, 0L, 5L, 15L, 0L, 10L, 10L, 0L, 5L, 8L, 5L, >>> 0L, 20L, 0L, 8L, 0L, 0L, 7L, 0L, 0L, 15L, 0L, 0L, 0L, 0L, 2L, >>> 0L, 2L, 0L, 2L, 0L, 3L, 3L, 4L, 5L, 0L, 0L, 8L, 2L, 2L, 3L, 0L, >>> 1L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, 12L, 0L, 0L, 10L, 0L, 0L, 5L, >>> 12L, 0L, 0L, 0L, 0L, 10L, 5L, 5L), course.root = c(0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 3L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 8L, 0L, 0L, 0L, 0L, 0L, 0L, 10L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 20L, 0L, 0L, 10L, 20L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 1L, 4L, 0L, 0L, 0L, 1L, 0L, 0L, 3L, 0L, 0L, 0L, 0L, 0L, >>> 5L, 0L, 0L, 0L, 0L, 0L, 5L, 0L, 0L, 0L, 5L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L), wood = c(2L, 0L, 0L, 1L, 0L, 2L, 1L, 0L, 2L, 1L, >>> 20L, 25L, 0L, 0L, 0L, 30L, 0L, 0L, 5L, 0L, 0L, 0L, 2L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 2L, 8L, 0L, 0L, 0L, 5L, 2L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 10L, 0L, 10L, 8L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 1L, 0L, 3L, 0L, 0L, 0L, 5L, 2L, 0L, 2L, 0L, 0L, 0L, 0L, 2L, 0L, >>> 1L, 0L, 0L, 25L, 5L, 0L, 0L, 5L, 10L, 10L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 30L, 8L, 5L, 0L, 0L, 0L, 0L), leaf = c(0L, >>> 0L, 0L, 0L, 0L, 0L, 3L, 0L, 2L, 2L, 1L, 2L, 1L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 1L, 0L, 0L, 5L, 5L, 2L, 10L, >>> 4L, 0L, 0L, 3L, 10L, 5L, 2L, 10L, 0L, 0L, 0L, 0L, 5L, 0L, 10L, >>> 5L, 0L, 0L, 10L, 5L, 3L, 1L, 0L, 10L, 0L, 5L, 3L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 10L, 5L, >>> 3L, 0L, 5L, 0L, 5L, 10L, 10L, 10L, 10L, 10L, 5L, 5L, 3L, 5L, >>> 3L, 3L, 8L, 10L, 3L, 0L, 0L, 5L, 5L), leaf.sand = c(0L, 0L, 0L, >>> 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 10L, 0L, 2L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 3L, 3L, 0L, 10L, 20L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, >>> 2L, 0L, 0L, 0L, 2L, 1L, 0L, 0L, 0L, 2L, 2L, 0L, 3L, 0L, 1L, 0L, >>> 0L, 10L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 2L, 2L, 2L, 2L, 0L, 3L, >>> 0L, 0L, 0L, 0L), veg = c(0L, 1L, 2L, 13L, 8L, 7L, 15L, 3L, 6L, >>> 10L, 0L, 2L, 2L, 4L, 1L, 0L, 0L, 0L, 3L, 0L, 3L, 0L, 0L, 0L, >>> 5L, 4L, 2L, 5L, 30L, 25L, 10L, 10L, 2L, 10L, 0L, 10L, 10L, 5L, >>> 8L, 3L, 10L, 10L, 0L, 5L, 12L, 10L, 5L, 10L, 8L, 15L, 20L, 20L, >>> 20L, 6L, 20L, 20L, 10L, 15L, 13L, 0L, 0L, 2L, 0L, 1L, 0L, 0L, >>> 0L, 1L, 0L, 3L, 0L, 2L, 2L, 0L, 1L, 0L, 0L, 0L, 5L, 0L, 0L, 0L, >>> 10L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L), pool = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 6L, 0L, 0L, 0L, 0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("sample.", >>> "date", "Replicate", "site", "sand.silt", "gravel", "cobble", >>> "boulder.bedrock", "fine.root", "course.root", "wood", "leaf", >>> "leaf.sand", "veg", "pool"), class = "data.frame", row.names = c(NA, >>> -100L))) >>> >>> >>> >> > > > > -- > Stephen Sefick > > Let's not spend our time and resources thinking about things that are > so little or so large that all they really do for us is puff us up and > make us feel like gods. We are mammals, and have not exhausted the > annoying little problems of being mammals. > > -K. Mullis > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/data-summary-and-some-automated-t.tests.-tp23562752p23585667.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.