Answers

1. Key principles include developing clear hypotheses, choosing proper success metrics, following a structured testing process, minimizing biases, and leveraging analytics tools to gather data.
2. Common experiments include A/B testing, funnel analysis, cohort analysis, multivariate testing, and using analytics tools. Each provides unique insights.
3. Use techniques such as A/B testing, blinding, and randomness to isolate variables and reduce bias. Determine appropriate sample sizes for statistical significance.
4. A growth mindset views setbacks as opportunities to refine hypotheses and ideas. It encourages iteration rather than giving up when results underwhelm.
5. Analytics tools collect quantitative and qualitative data on user behaviors and product performance to extract insights from experiments.
6. Sound analysis examines statistical significance, looks for qualitative insights, checks alignment with hypotheses, reproduces results, and synthesizes learnings for...