[R] Using statistical test to distinguish two groups

[Achim Zeileis]

On Wed, 5 May 2010, Ralf B wrote:

> Hi R friends,
>
> I am posting this question even though I know that the nature of it is
> closer to general stats than R. Please let me know if you are aware of
> a list for general statistical questions:
>
> I am looking for a simple method to distinguish two groups of data in
> a long vector of numbers:
>
> list <- c(1,2,3,2,3,2,3,4,3,2,3,4,3,2,400,340,3,2,4,5,6,4,3,6,4,5,3)
>
> I would like to 'learn' that 400,430 are different numbers by using a
> simple approach.

It seems that you want to cluster the data. There are, of course, loads of 
clustering algorithms around, see e.g.,
   http://CRAN.R-project.org/view=Cluster

In this simple example a standard hierarchical clustering approach shows 
you what you're after.

## data
list <- c(1,2,3,2,3,2,3,4,3,2,3,4,3,2,400,340,3,2,4,5,6,4,3,6,4,5,3)

## cluster using Ward method for Euclidian distances
hc <- hclust(dist(list, method = "euclidian"), method = "ward")
plot(hc)
hc

## cut into two clusters
split(list, cutree(hc, k = 2))

hth,
Z

> The outcome of processing 'list' should therefore be:
>
> listA <- c(1,2,3,2,3,2,3,4,3,2,3,4,3,2,3,2,4,5,6,4,3,6,4,5,3)
> listB <- c(400,340)
>
> I am thinking a non-parametric test since I have no knowledge of the
> underlying distribution. The numbers are time differences between two
> actions recorded from a the same person over time. Because the data
> was obtained from the same person I would naturally tend to use
> Wilcoxon Signed-Rank test. Any thoughts on that?
>
> Are there any R packages that would process such a vector and use
> non-parametric methods to split or divide groups based on their
> values? Could clustering be the answer given that I already know that
> I always have two groups with a significant difference between the
> two.
>
> Thanks a lot,
> Ralf
>
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