About statistics-skills
A collection of statistical analysis skills for researchers and practitioners, with guides spanning inference, testing, modeling, and experiment planning. Users select a relevant skill and consult its instructions.
Key features
- 01Bayesian inference and model comparison
- 02Anomaly detection
- 03Hypothesis testing and power analysis
- 04Meta-analysis and heterogeneity assessment
- 05Statistical modeling and causal inference
- 06Survival analysis and structural equation modeling
Use cases
- 01Plan reproducible ML experiments
- 02Find outliers in research data
- 03Estimate sample size and statistical power
- 04Conduct survival or nonparametric analysis
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/statistics-skillsin Claude Code to confirm it loaded.
Details
From the project READMEStatistical Analysis — 10 Skills
Select the skill matching the user's need, then read its SKILL.md.
| Skill | Description |
|---|---|
| bayesian-statistics-guide | Bayesian inference methods including prior selection, MCMC, and model comparison |
| data-anomaly-detection | Detect anomalies and outliers in research data using statistical methods |
| hypothesis-testing-guide | Statistical hypothesis testing, power analysis, and significance reporting |
| meta-analysis-guide | Conduct systematic meta-analyses with effect size pooling and heterogeneity |
| ml-experiment-tracker | Plan reproducible ML experiment runs with parameters and metrics tracking |
| modeling-strategy-guide | Strategic statistical modeling, experimentation, and causal inference |
| nonparametric-tests-guide | Apply Mann-Whitney, Kruskal-Wallis, and other nonparametric methods |
| power-analysis-guide | Sample size calculation and statistical power analysis guide |
| sem-guide | Structural equation modeling with latent variables guide |
| survival-analysis-guide | Conduct Kaplan-Meier, Cox regression, and time-to-event analyses |
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