Your question is A/B Test Recommendation for Signup. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You ran an A/B test on a signup flow change and need to give a quick recommendation to a product manager. The control had 24,800 users and 2,232 signups, while the treatment had 25,100 users and 2,410 signups. Assume a 5% significance level and that signup conversion is the primary decision metric.
How would you analyze these results and explain, in a concise recommendation, whether the treatment should be rolled out?