Sampling Methodology & Statistical Design
$39
Included with membership · or buy it individually
Sampling Methodology & Statistical Design
Design statistically valid sampling strategies for M&E data collection. Covers probability and non-probability sampling, sample size calculation, stratification, clustering, and power analysis. Essential for any quantitative data collection.
Installs into Claude Code, opencode, Claude.ai, ChatGPT, Gemini. Members get the full library.
It triggers on
- sampling methodology
- sample size
- how many respondents
- sampling frame
- random sampling
- stratified sampling
- cluster sampling
- power calculation
- confidence interval
- margin of error
- representative sample
What it produces
- Generate Sampling Plan
- Calculate Sample Size
Pairs with: survey-design, evaluation-design, data-quality-assessment, qualitative-methods.
From download to answer in three steps.
Download & unzip
You get a folder with SKILL.md, its references and a cheatsheet.
Install it
Drop it in your skills directory (Claude Code / opencode), or upload SKILL.md to a Project, Custom GPT or Gem.
Ask
Ask in this domain. It answers from the source, cites the section, or says [NOT IN SOURCE].
Before you install.
What exactly is a skill?
A skill is a folder your AI loads on demand: a SKILL.md with the method, reference files, a cheatsheet and a provenance manifest. The model answers from it and replies [NOT IN SOURCE] instead of inventing.
Which AIs does it work with?
This skill installs into Claude Code, opencode, Claude.ai, ChatGPT, Gemini — and any tool that reads a SKILL.md.
Will it answer from the source?
Yes. Every package carries explicit answering rules: cite the section for each claim, label authority vs reasoning, and never invent a figure, citation or rule.
Is it kept current?
Yes. Method and donor skills are reviewed quarterly and you can re-download the latest version from your dashboard.
Sampling Methodology & Statistical Design
Design statistically valid sampling strategies for M&E data collection.