# Fisher's exact test in R

First, I am no expert but I am analyzing some marketing data. 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. I want to know if one of the site variation performs better at generating more filled out forms.

Sample data:

dat2 = matrix(c(10,50,35,40), ncol=2)
dat2
Site 1                Site 2
Filled out form                10                    35
Did not fill out form          50                    40

> 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 1 at a statistically significant threshold.

Given the problem, am I performing the correct test?

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