I would love some help with interpreting a non-parametric test. I have data on the # of seed heads produced by an invasive plant species (n=80 plants). I applied a grazing treatment in an attempt to reduce the number of seeds produced by this invasive plant (targeted grazing treatment). I harvested 40 plants post-targeted grazing, and 40 plants within a control, ungrazed enclosure.
Most plants within the targeted enclosure were grazed, and had values of 0. My data was not normal, so I used a Wilcoxon rank sum test with continuity correction. My null hypothesis is that there is no difference in # of seed heads between the grazing treatment and the control, ungrazed group.
Here is my code for that exact test:
wilcox.test(Seedheads~Treatment,mu=0,alt="two.sided",conf.int=T,conf.level=0.95,paired=F,exact=T,correct=T)
Please see below the output of this test:
W = 1384.5, p-value = 4.94e-09
alternative hypothesis: true location shift is not equal to 0
95 percent confidence interval:
7.999998 30.000030
sample estimates:
difference in location
22.99994
From my understanding, the p-value is much smaller than .05, so I reject the null hypothesis. There is a significant difference in the number of seedheads. Is my understanding of this correct? Could I state that my p-value is <0.05 when discussing my results?