Hi,
I am new to R and have not had the most exposure to statistics.
I have a dataset of percentage cover (so 0-100) for certain species in 3
different shore zones (High, mid and low). The data was recorded for
different protected areas as well (17 of them) and my number of obs is
large (3358). I'm obviously interested in the difference in percentage
cover of species between shore zones as well as between protected areas.
The problem is that my data contains loads of zeros and I haven't dealt yet
in statistics with how to manipulate the data so as to perform robust tests
on it. I previously used Kruskal-Wallis ANOVAs to look at cover differences
in shore zone but I am worried that it is inappropriate because of the
large sample size that I have and because my variances are not equal.
I've read a bit about using a zero-inflated negative binomial regression to
fit to my data, but I'm not sure if that will work because it is for count
data.
I would very much appreciate it if someone could point me in the correct
direction wrt a transformation that may help or an appropriate model to fit
or test to use. I've searched quite a bit but I'm a out of my depth.
PS sorry if I sound like a halfwit
Thanks a lot
Ben
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