See below for the output of python and R.
Why there is a difference in the odds ratio? Given that R is most
widely used by statisticians, I'd prefer the python version print the
same results. Also, confidence intervals are missing in the python's
output.
>>> stats.fisher_exact([[8, 2], [1, 5]])
(20.0, 0.03496503496503495)
R> fisher.test(rbind(c(8, 2), c(1,5)))
Fisher's Exact Test for Count Data
data: rbind(c(8, 2), c(1, 5))
p-value = 0.03497
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
1.008849 1049.791446
sample estimates:
odds ratio
15.46969
--
Regards,
Peng
