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.
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?