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.
日本語の概要は準備中です。原文の説明を表示しています。
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)まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
日本語の概要は準備中です。原文の説明を表示しています。
Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Post-analysis learning and process improvement. Use when completing major analysis projects, documenting lessons learned, or improving team analytical practices.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。