data-stats-analysis
Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
npx skills add majiayu000/claude-skill-registry --skill data-stats-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Statistical Analysis (Universal) ## Overview This skill enables you to perform rigorous statistical analyses including t-tests, ANOVA, correlation analysis, hypothesis testing, and multiple testing corrections. Unlike cloud-hosted solutions, this skill uses standard Python statistical libraries (**scipy**, **statsmodels**, **numpy**) and executes **locally** in your environment, making it compatible with **ALL LLM providers** including GPT, Gemini, Claude, DeepSeek, and Qwen. ## When to Use This Skill - Compare means between groups (t-tests, ANOVA) - Test for correlations between variables - Perform hypothesis testing with p-value calculation - Apply multiple testing corrections (FDR, Bonferroni) - Calculate statistical summaries and confidence intervals - Test for normality and distribution fitting - Perform non-parametric tests (Mann-Whitney, Kruskal-Wallis) ## How to Use ### Step 1: Import Required Libraries ```python import numpy as np import pandas as pd from scipy import stats from scipy.stats import ttest_ind, mannwhitneyu, pearsonr, spearmanr from scipy.stats import f_oneway, kruskal, chi2_contingency from statsmodels.stats.multitest import multipletests from statsmodels.
- Overview
- When to Use This Skill
- How to Use
- Step 1: Import Required Libraries
- Step 2: Two-Sample t-Test
- Step 3: One-Way ANOVA
- Step 4: Correlation Analysis
- Step 5: Multiple Testing Correction
- Step 6: Non-Parametric Tests
- Advanced Features
- Normality Testing
- Chi-Square Test for Contingency Tables
- Confidence Intervals
- Effect Size Calculation
What does the data-stats-analysis skill do?
Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill data-stats-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.