CAPM Practice: Validate requirements through product delivery

Requirements defined as hypotheses (if we build X, user behavior Y will change by Z%) enable post-delivery validation: measure actual outcomes against the hypothesis. This evidence-based approach produces definitive answers about whether requirements were correctly specified and whether the solution delivered value.

**Why not A:** Statistical hypothesis testing is a mathematical technique for analyzing data distributions, not the same as hypothesis testing in post-delivery validation. Requirements-based hypothesis testing compares expected business outcomes with actual measured results to assess whether the solution achieved its purpose.

**Why not C:** Hypothesis testing in requirements validation is applicable to all product delivery, not just research projects. Any feature can be framed as a hypothesis (if we build X, outcome Y will change by Z%), making it a broadly useful validation approach for commercial products and internal tools alike.

**Why not D:** Testing stakeholder hypotheses about users before delivery is part of discovery and elicitation, not post-delivery validation. Post-delivery hypothesis testing specifically measures actual outcomes after the solution is deployed to determine whether it achieved the intended results.