This tool assumes a normal distribution and uses difference of means to compute confidence.
What is the difference between a G test and a T test? What are the benefits or downsides to using each method to measure the effectiveness of our A/B tests?
I'm trying to figure out which one I should use to measure the results of my A/B test framework. Our framework has two general use cases: split the group of visitors evenly, show each one a different feature and measure their conversion on some other page (say, the sign up page); and split the group of visitors into the control group (90%) and an experimental group (10%) for a test, and measure conversions on some other page.
Our website gets between 1000 and 200,000 visits per day. These visits are split with an exponential distribution across about 300 pages.