| name | pingouin-stat |
| description | Main Pingouin statistics workflow for psychology research. Use when the user says pingouin-stat or asks to analyze psychology data with Pingouin end-to-end: first clarify research question, variables, assumptions, output format such as Word/PDF/LaTeX, table/figure requirements, then route to analysis skills, run approval checks, and organize final results. |
Pingouin Stat
This is the main entry point. Use it instead of asking users to choose individual sub-skills.
Load
Read in order:
../../references/intake-checklist.md../../references/workflow-index.md../../references/supervision-gates.md
Read ../../references/archive-contract.md before generating code or a deliverable that must be reproducible.
Read ../../references/workflow-contract.md for a resumable multi-command run.
Read ../../references/pingouin-optimization.md before generating concrete Pingouin code.
Read ../../references/pingouin-api-quickref.md only when generating code. Read ../../references/apa-output-template.md only when writing final prose or tables.
Workflow
- Intake: clarify only missing items that affect the analysis.
- Route: choose one or more downstream skills from
workflow-index.md.
- Screen: use
pg-data-screening when data shape, missingness, or assumptions are unknown.
- Analyze: call the selected analysis workflow or generate the relevant Pingouin code.
- Approve: run
pg-analysis-approval before final interpretation.
- Organize: use
pg-reporting to produce the requested deliverable shape.
- Archive: initialize a run under
archive/analysis-runs/, save the exact code and numerical outputs, then write the report and S0–S5 audit record.
Intake Contract
If key information is missing, ask a compact question set covering:
- Research hypothesis.
- Data path or available columns.
- Outcome, predictor, subject ID, covariates/mediators/raters/items.
- Between/within/repeated/nested structure.
- Planned or exploratory tests.
- Output format: Markdown, Word/docx, PDF, LaTeX, CSV tables, notebook/script.
- Figure/table requirements.
- Language and reporting standard.
If the user says "你先决定" or provides enough context, proceed with explicit assumptions.
Routing Output
Before analysis, produce this short plan:
Intake: <known + missing/assumed>.
Route: <skill(s)> -> <Pingouin function(s)>.
Approval gates: S0-S5 will be checked before interpretation.
Deliverable: <format/language/tables/figures>.
Next: <ask question / run screening / generate code>.
Result Assembly
Final result should include only the sections that fit the user's requested format:
- Analysis plan.
- Data screening summary.
- Main statistical result.
- Follow-up comparisons.
- Figure/table code or rendered table.
- APA/Chinese prose.
- Approval findings.
- Reproducible Python code.
Guardrails
- Do not skip approval when producing conclusions.
- Do not invent results when no data/output exists.
- Do not force Pingouin onto designs requiring mixed-effects models, SEM, count models, survival analysis, or complex survey models.
- Use short S0-S5 audit codes by default; expand only failed gates or user-requested rationale.
- Do not finish a code-generating run without saving the code, output references, and audit record under one archive run directory.
