statistical-analysis

Identify and summarize statistical claims in scientific texts and assess their credibility.

1|Updated Apr 23, 2026

Search Tags:#reproducibility #p-values #statistical-analysis #confidence-intervals #experimental-design

Ready to run

npx skills add https://github.com/Avaivartika/jiaoleaf-ai --skill statistical-analysis-avaivartika

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: statistical-analysis
Source: https://github.com/Avaivartika/jiaoleaf-ai/tree/main/extension/skills/science/statistical-analysis
Command: npx skills add https://github.com/Avaivartika/jiaoleaf-ai --skill statistical-analysis-avaivartika

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The skill helps researchers and reviewers systematically verify the accuracy and transparency of statistical reporting in scientific manuscripts, reducing the risk of misleading conclusions.

Core Features & Use Cases

Check the presence and correctness of methodological details such as sample size, variance, and number of replicates.
Verify the reporting of p-values, confidence intervals, baselines, ablations, and the description of statistical tests.
Use this skill during peer-review or internal manuscript audits to improve reproducibility and credibility.

Quick Start

Identify the statistical claims in the attached manuscript and generate a concise audit report.

Frequently Asked Questions about statistical-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I audit statistical claims and p-values in a scientific paper?▼

To audit statistical claims, you can systematically verify the reporting of p-values, confidence intervals, and statistical tests within a manuscript to assess their credibility and reproducibility.

What is checked during a statistical reporting audit for experimental design?▼

A statistical reporting audit checks for the presence and correctness of methodological details such as sample size, variance, number of replicates, baselines, and ablations across results and methods sections.

How do I check if confidence intervals and sample sizes are reported correctly in a manuscript?▼

You can check reporting sufficiency by enforcing requirements for sample size, variance, confidence intervals, and statistical tests, ensuring transparent baselines are described without fabricating missing data.

Can I use this approach to verify reproducibility across different scientific disciplines?▼

Yes, you can verify reproducibility across disciplines because the scope covers results sections, methods, and supplementary materials universally, focusing on reporting sufficiency and avoiding fabrication.

What is the best way to review statistical methods during peer review?▼

The best way to review statistical methods is to identify claims in the text and generate a concise audit report that flags missing variance, replicates, or incorrect p-value reporting.