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/methodology-explainer

@e4e97c5

Explain analysis methodology to diverse audiences. Use when documenting 'how we did this' sections, building trust through transparency, or teaching analytical approaches to stakeholders.

Use this Skill: https://skilld.dev/gh/nimrodfisher/data-analytics-skills/methodology-explainer

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assetsmethodology_slide_template.md

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Methodology Slide Template

Use this structure when the methodology needs to be presented rather than read. One slide per section is the norm; collapse sections for shorter presentations.


Slide 1: How We Answered This Question

Title: How we measured [metric / question]

Content (3 bullet points max):

  • Data: [source and time period in one line]
  • Method: [approach in one plain-language sentence]
  • Confidence: [High / Medium / Low — with one-line rationale]

Speaker notes: [full explanation for the presenter; what to say if asked to elaborate]


Slide 2: What the Data Covers (optional — include only if scope is non-obvious)

Title: What's in and out of scope

In scope Out of scope
[e.g. paying customers] [e.g. trial accounts]
[e.g. Jan 2024 – Mar 2024] [e.g. backfilled historical data]

Slide 3: Key Assumptions (include when assumptions materially affect the conclusion)

Title: What we assumed

Assumption Why reasonable If wrong, impact is...
[assumption] [rationale] [consequence]

Slide 4: What This Analysis Cannot Tell Us

Title: Limitations

  • [Limitation 1]: [plain-language implication]
  • [Limitation 2]: [plain-language implication]

Closing line: "For these questions, we would need [data / experiment / different approach]."


Design Notes

  • Keep text to the minimum needed for a non-attending reader to follow
  • No statistical notation on slides unless the audience is Tier 3
  • Use "We measured X by doing Y" — active voice, first person plural
  • Avoid "methodology" as the slide title; use a specific verb instead ("How we measured...", "What data we used...")

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub16d

    The skill is a collection of markdown templates and guidelines for explaining data analysis methodologies. It does not contain any executable code, remote dependencies, or risky behaviors.

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    No alerts

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    Risk: LOW · No issues

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    Score: 93/100 · 2 sections analyzed

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Last checked against GitHub 6 days ago.

Activeupdated 5 months ago

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