skills/dkyazzentwatwa/chatgpt-skills/statistical-power-calculator

statistical-power-calculator

SKILL.md

Statistical Power Calculator

Calculate statistical power and determine required sample sizes for hypothesis testing and experimental design.

Purpose

Experiment planning for:

  • Clinical trial design
  • A/B test planning
  • Research study sizing
  • Survey sample size determination
  • Power analysis and validation

Features

  • Power Calculation: Calculate statistical power for tests
  • Sample Size: Determine required sample size for desired power
  • Effect Size: Estimate detectable effect size
  • Multiple Tests: t-test, proportion test, ANOVA, chi-square
  • Visualizations: Power curves, sample size charts
  • Reports: Detailed analysis reports with recommendations

Quick Start

from statistical_power_calculator import PowerCalculator

# Calculate required sample size
calc = PowerCalculator()
result = calc.sample_size_ttest(
    effect_size=0.5,
    alpha=0.05,
    power=0.8
)
print(f"Required n per group: {result.n_per_group}")

# Calculate power
power = calc.power_ttest(n_per_group=100, effect_size=0.5, alpha=0.05)

CLI Usage

# Calculate sample size for t-test
python statistical_power_calculator.py --test ttest --effect-size 0.5 --power 0.8

# Calculate power
python statistical_power_calculator.py --test ttest --n 100 --effect-size 0.5
Weekly Installs
38
GitHub Stars
24
First Seen
Jan 24, 2026
Installed on
opencode29
claude-code29
gemini-cli28
codex27
cursor26
github-copilot23