Let's say I have 4 plants and I measure something
under 2 conditions. For example:
The entries in the table show how many times I saw something
under condition (C1 or C2) for plant (P1, P2, P3 or P4).
P1, P2, P3, P4 C1 0 20 0 19 C2 100 80 180 150
Now I would like to answer the question "what is the probability that these 39 times of seeing something
is unevenly distributed between these 4 plants"?
I am much interested in observation like this, rather than, say:
P1, P2, P3, P4 C1 25 20 15 19 C2 100 80 180 150
Is it right to use Fisher's exact test for this? I just extended the question from a 2*2 table to 2*4.
something
under C1, and that 100, 100, 180 and 169 of them are from P1, P2, P3 and P4 respectively, What is the probability that these 39something
are so unevenly distributed between the 4 plants? And this is what I desire. I agree the second table is a bit misleading. It might or might not be significant (depending on the parameters that fisher's exact test computes). $\endgroup$39 something
under C1, what is the probability that there are none of them from P1 and P3 and 20 and 19 of them from P2 and P4? This I suppose would be far from random distribution and hence a very significant p-value. Did I misunderstand something here? $\endgroup$