Standards, templates, and checklists for reproducible exploratory analysis, hypothesis generation, and validation.
A practical, reproducible checklist for exploratory data analysis (EDA) that reduces false discoveries, captures provenance, and creates a clear handoff to confirmatory testing and decision making.
A practical, step-by-step checklist and runbook to make exploratory analysis reproducible, defensible, and easy to hand off — including notebook metadata, data provenance, validation plans, privacy checks, and a compact handoff template for decisions.
A practical, step-by-step checklist to move from an exploratory observation to a validated insight that can support confident decisions. For each step the checklist describes what to check, example evidence to produce, and a minimal pass/fail criterion.
Interactive checklist and hypothesis log to capture EDA findings, confirm reproducibility and data quality, and convert observations into prioritized, testable hypotheses with owners and next steps.