methodology-explainer

name	methodology-explainer
description	Create a clear, transparent explanation of analytical methodology for any audience level. Activate when you deliver findings that require the audience to trust the method — A/B tests, attribution models, forecasts, statistical analyses, or anything where "how did you get that?" is a likely question.

When to use

• Delivering A/B test results where the statistical method needs justification
• Presenting a forecast or model where assumptions must be communicated
• Documenting methodology for reproducibility and audit
• Onboarding a stakeholder who needs to understand and trust a recurring analysis
• Any analysis where "how did you get that?" is a likely question

Process

1. Determine audience tier — classify as executive (decision-maker, no stats background), analyst (technically literate peer), or technical peer (will scrutinise the method). Tier determines depth and format.
2. Select explanation pattern — choose: narrative (for executives), layered technical (for analysts — plain first, then detail on request), or Q&A format (for peer review). See references/explanation_patterns.md.
3. Draft the core explanation — cover: what question the analysis answers, what data was used, what method was applied, what assumptions were made, and what the key limitations are
4. Simplify statistical language — replace p-values with confidence statements, model metrics with error margins, technical method names with purpose descriptions. See references/stats_plain_language.md.
5. Add a limitations section — every methodology explanation must include what the analysis cannot conclude and what would change the findings
6. Produce deliverables — fill assets/methodology_writeup_template.md or assets/methodology_slide_template.md depending on format

Inputs the skill needs

• Required: the method to explain — choose from the built-in list: wilson_score, iqr_outlier, z_score, linear_regression, kmeans
• Required: target audience — field_staff | manager | council | public
• Optional: known concerns or questions the audience is likely to raise
• Optional: format requirements (slide, written doc, email)

Quick start (script — no external data required):

python3 scripts/explain_method.py --method wilson_score --audience manager
python3 scripts/explain_method.py --method z_score --audience council

The script prints the formula, plain-language explanation, an NYC DOT example, and the audience-tailored phrasing. For custom methods not in the list, use the templates in assets/ directly.

Output

• Plain-language methodology write-up
• Limitations paragraph
• assets/methodology_writeup_template.md or assets/methodology_slide_template.md (filled)