Research Data Analysis

Read First

• references/repository-contract.md

• references/output-contracts.md

Workflow

1. Identify raw, interim, and processed data paths.
2. Read data dictionary and provenance notes.
3. Write reusable analysis logic in

   src/

   , not only notebooks.
4. Use scripts or CLI entrypoints for repeatable runs.
5. Put generated tables in

   outputs/tables/

   and figures in

   outputs/figures/

   .
6. Record important findings in

   wiki/claims/

   or

   wiki/experiments/

   .
7. Link paper claims to exact table, figure, or experiment artifacts.

Statistical Discipline

• Match tests to design, distribution, sample size, and hypothesis.
• Report effect sizes and confidence intervals when relevant.
• Distinguish statistical significance from practical significance.
• Flag multiple comparisons, missing data, selection bias, and confounds.
• Do not treat exploratory analysis as confirmatory.

Figure Discipline

• Use readable labels, units, captions, and colorblind-safe palettes.
• Avoid misleading axes and decorative chart types.
• Save source data for final figures when practical.
• For publication figures, record command and input dataset.

Notebook Policy

src/