Fisher Exact Test
On 11/17/2011 06:29 PM, Abraham Mathew wrote:
I have information on two versions of the same site, and I have data
on the number of times people filled out a form on each version
of the site.
Sample data:
Site 1 Site 2
Filled out form 10 35
Did not fill out form 50 40
dat2 = matrix(c(10,50,35,40), ncol=2)
dat2
fisher.test(dat2)
fisher.test(dat2)
Fisher's Exact Test for Count Data data: dat2 p-value = 0.0002381 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 0.09056509 0.54780215 sample estimates: odds ratio 0.2311144 I'm really not sure if I set up the test properly, but I can obviously reject the null hypothesis given the low p-value. Site 2 converts better than site 2 at a statistically significant threshold. Am I running my code wrong?
Your code is fine; your conclusion is valid (assuming you mean "...better than site 1...").
Patrick Breheny Assistant Professor Department of Biostatistics Department of Statistics University of Kentucky