Hey (:)<p>You'd be surprised how many of the (quite talented) data analysts I've worked with don't truly understand the beautiful simplicity of Bayesian AB testing.<p>When AB testing, most metrics we care about are binomial (i.e., did or didn't happen -> 1 or 0). Think "User clicked login" or "User upgraded to Premium".<p>This means if you want to build an API for statistically analyzing these experiments all you need as inputs are 4 numbers (per metric):
- Control: Total users, and users who "did"
- Variant: Total users and users who "did"<p>Then you can reconstruct the "observation array" on the other side of the API, statistically compare your control to your variant, and send the results back!<p>Right now, if you have a way to pull those 4 numbers from Amplitude, or your database, you can run a Bayesian analysis using the analyzer i built.<p>Have fun!<p>rate limits do apply, product translation sold separately