experiment-doc-builder

To ensure statistical significance, your experiment design must calculate the required sample size and timeline before launch. This Skill validates your experiment brief to guarantee it reaches statistical significance for reliable product testing results.

Causal hypothesis validity ensures your predicted outcome is directly linked to the metric you are testing. This Skill guides you through pressure-testing your hypothesis to confirm causal relationships rather than mere correlations in data analysis.

You build an experiment brief by scoring it on clarity, measurability, impact, feasibility, and learning value. A minimum rigor score of 70 is required for approval, ensuring high-quality data analysis for user engagement.

You need an understanding of statistical concepts and the ability to apply them practically. This Skill handles the complex calculations for sample size and statistical significance, but foundational knowledge is required for proper experiment design.

Your hypothesis testing lacks rigor if it fails to establish causal links or meet the minimum score across clarity, measurability, impact, feasibility, and learning value. This Skill scores your brief and requires a minimum of 70 for approval.