pingouin-stat

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:

1. ../../references/intake-checklist.md
2. ../../references/workflow-index.md
3. ../../references/supervision-gates.md

Read ../../references/pingouin-api-quickref.md only when generating code. Read ../../references/apa-output-template.md only when writing final prose or tables.

Workflow

1. Intake: clarify only missing items that affect the analysis.
2. Route: choose one or more downstream skills from workflow-index.md.
3. Screen: use pg-data-screening when data shape, missingness, or assumptions are unknown.
4. Analyze: call the selected analysis workflow or generate the relevant Pingouin code.
5. Approve: run pg-analysis-approval before final interpretation.
6. Organize: use pg-reporting to produce the requested deliverable shape.

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.