You're running product experiments on surfaces like Asana Inbox, task creation, or project onboarding. The team wants results quickly, but shorter tests and repeated looks at the data can weaken inference.
How would you think about the trade-off between faster experimentation and statistical rigor?
How you balance iteration speed against false positive riskWhether you understand power, MDE, and sample size trade-offsWhether you recognize the danger of peeking and optional stopping