Structure analysis approach before starting work. Use when receiving new analysis requests, breaking down complex questions into steps, or planning iterative analysis workflows.
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After requirements are gathered and before any data is touched. Planning is especially important when the analysis involves multiple steps, uncertain data availability, or a tight deadline where sequencing matters. A 15-minute planning session prevents hours of wrong-direction work.
references/scoping_framework.md; each sub-question should be answerable with a single data pull or calculation.references/effort_estimation.md to assign time estimates per step; sum to a total and compare against the deadline.references/risks_dependencies.md to document anything that could delay or invalidate the plan (data gaps, external approvals, methodology uncertainty).assets/analysis_plan_template.md; for projects with stakeholder kickoffs use assets/kickoff_doc_template.md.stakeholder-requirements-gathering skill)analysis_plan_template.md)kickoff_doc_template.md)No reviews yet. Tell others what you thought.
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Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
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Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
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Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.
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Pre-delivery quality assurance for analysis work. Use when reviewing analysis before sharing with stakeholders, checking for completeness, validating assumptions, or ensuring clarity of recommendations.
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Post-analysis learning and process improvement. Use when completing major analysis projects, documenting lessons learned, or improving team analytical practices.
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Standard business metric calculation with industry benchmarks. Use when calculating SaaS metrics (MRR, churn, LTV, CAC), e-commerce KPIs, or product analytics metrics with proper definitions.
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