Is Mann Whitney U the right statistical test for this analysis? I am studying the spatial interactions between coral at a specific reef. I have the abundances of each coral species at each site we studied. I also have already run statistical tests and basically have finalized which coral species are in significant interactions with other coral species at each site. I now want to see if abundance of coral species has any impact on if they are in a significant interaction for each site. I have turned to the Mann Whitney U test as my data is not normalized and I have unequal sample sizes. For example I have made up some fake data for what this looks like:




Site Number
Abundance
Significance




1
24
yes


2
2
no


3
10
yes


4
8
no


5
34
yes


6
17
yes


7
4
no


8
5
yes


9
4
no


10
25
yes




I have then run this code:
wilcox.test(Abundance ~ Significance, data = dat, exact = F)

This is to see if there is a statistical significance between the abundances of this coral species when in a significant interaction and when not.
Is this a good way about doing this or should I be doing a different statistical test?

First tried as comment but too long:
What you intend to do may be somehow not the right strategy:
But first the assumptions:

*

*You measured the abundance of corals at different sites (in your example 10 sites).


*Then you already calculated if there is a significant correlation between different coral species at this site.


*Now you want to estimate if there is a relationsship between the abundance of corals measured at each site and the significant correlation between different coral species.
In other words if you already found a significant relationship between different coral species at one site you hypothesize that the abundance is high.
With a Mann-Whitney U test you test two groups e.g. Significant vs not significant in terms of Abundance.
This if I do not miss something is not correct and proned to counfounding.
