[R] data summary and some automated t.tests.

Sun May 17 19:36:20 CEST 2009

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 <ligges at 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 at 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.
> 
> 

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