Problem
Scenario
You are planning a customer survey or product experiment and need to decide whether the design is adequately powered before launch. The team wants confidence that the study can detect a meaningful change without over-sampling or drawing conclusions too early.
Question
How would you think about sample size and statistical power for this survey or experiment? Walk through how you would choose an MDE, define the primary metric and guardrails, and decide whether the planned test is large enough to support a decision.
What matters
- Primary metric must be defined before sizing the test
- MDE should reflect a meaningful business or user impact
- Guardrails prevent shipping a treatment that improves one metric while harming others
- Power depends on baseline rate, variance, alpha, and desired detectable lift
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