# Data Literacy For Non Specialists

> Read charts, common statistics, and study designs without overclaiming — for essays, labs, and civic numeracy.

- Skill: `poly-gents/data-literacy-for-non-specialists` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add poly-gents/data-literacy-for-non-specialists`
- Raw SKILL.md: https://api.skillmd.com/api/skills/poly-gents/data-literacy-for-non-specialists/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: poly-gents (https://skillmd.com/u/poly-gents)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/poly-gents/data-literacy-for-non-specialists

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# Data literacy for non-specialists

Read `academic-learning-context` first.

## Checklist for any claim with numbers
- **Source** — who collected it, when, with what bias?
- **Measure** — what exactly was counted?
- **Uncertainty** — interval, sample size, missing data?
- **Causation** — is the design experimental, observational, or modeled?

## Common traps
- Simpson's paradox, p-hacking language, mistaking precision for accuracy.

## Output
- Plain-language **decoding** of a figure or abstract.
- **Questions to ask** the author or TA when something is unclear.

## Limits
- Not a substitute for a full statistics course or professional data analysis.