Suppose we have the following data set:
Men Women
Dieting 10 30
Non-dieting 5 60
If I run the Fisher exact test in R then what does alternative = greater (or
less) imply? For example:
mat = matrix(c(10,5,30,60), 2,2)
fisher.test(mat,alternative ="greater")
I get the p-value = 0.01588 and odds ratio = 3.943534. Also, when I flip
the rows of the contingency table like this:
mat = matrix(c(5,10,60,30), 2,2)
fisher.test(mat,alternative ="greater")
then I get the p-value = 0.9967 and odds ratio = 0.2535796. But, when I run
the two contingency table without the alternative argument (i.e.,
fisher.test(mat)) then I get the p-value = 0.02063.
1. Could you please explain the reason to me?
2. Also, what is the null hypothesis and alternative hypothesis in the
above cases?
3.
Can I run the fisher test on a contingency table like this:
mat = matrix(c(5000,10000,69999,39999), 2,2)
Thanks.
PS: I am not a statistician. I am trying to learn statistics so your help
(answers in simple English) would be highly appreciated.
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