Statistical Power

If you've ever been asked "how many subjects do you need?" in a grant or IRB form, this is the skill to reach for. It wraps statsmodels and SciPy behind one interface (`sample_size`, `mde`, `power`, `power_curve`) covering t-tests, ANOVA, proportions, correlations, chi-square, and regression, and it steers you toward a sensible effect size instead of letting you invent one. Its sharpest feature is the explicit warning against post-hoc "observed" power, which reviewers rightly reject. The simulation path for mixed models, GLMs, and cluster-randomized designs is where the real value lies, though you'll need a credible data-generating process to trust it. Layout decisions like randomization or blocking belong to a different skill.

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last updated: Jul 31, 2026

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Install

$ npx -y skills add K-Dense-AI/scientific-agent-skills --skill statistical-power --agent claude-code

Installs into .claude/skills of the current project.

Files

Statistical Power & Sample Size

Overview

Power analysis answers one of the most consequential questions in study planning: how large a sample do you need to reliably detect an effect of a given size, and what could you detect with the sample you can afford? An underpowered study wastes resources and produces inconclusive or irreproducible results; an overpowered one wastes participants, money, and (in clinical work) exposes more people to risk than necessary. Getting this right before data collection is the single highest-leverage statistical decision in a project.

Four quantities are locked together for any given test: sample size (n), effect size, significance level (α), and power (1 − β). Fix any three and the fourth is determined. Every calculation in this skill is some rearrangement of that relationship.

This skill covers the two ways to do power analysis:

Closed-form formulas (fast, exact for standard tests) — see references/closed_form_recipes.md.
Simulation / Monte Carlo (works for any design or model you can simulate and analyze) — see references/simulation_based_power.md.

SKILL.md on GitHub