This mean
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.

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?
Can anyone help?

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