power-analysis-calculator
Skill for statistical power analysis and sample size calculation
Best use case
power-analysis-calculator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Skill for statistical power analysis and sample size calculation
Teams using power-analysis-calculator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/power-analysis-calculator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How power-analysis-calculator Compares
| Feature / Agent | power-analysis-calculator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Skill for statistical power analysis and sample size calculation
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Power Analysis Calculator Skill ## Purpose Calculate statistical power and required sample sizes for experimental designs to ensure adequate study power. ## Capabilities - Calculate required sample size - Compute statistical power - Estimate effect sizes - Handle multiple comparisons - Support various designs - Generate power curves ## Usage Guidelines 1. Specify design type 2. Define effect size 3. Set alpha and power 4. Calculate sample size 5. Generate power curves 6. Document analysis ## Process Integration Works within scientific discovery workflows for: - Study planning - Grant proposals - Protocol development - Design optimization ## Configuration - Statistical test selection - Effect size specifications - Power thresholds - Output formatting ## Output Artifacts - Sample size calculations - Power analyses - Effect size estimates - Power curves
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