data-analysis

Run complete R data analysis workflows with reproducible outputs.

5|1|Updated Mar 15, 2026

Search Tags:#workflow #data analysis #regression #r #reproducibility #publication

Ready to run

npx skills add https://github.com/alohays/paper2pr --skill data-analysis-alohays

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/alohays/paper2pr/tree/main/.claude/skills/data-analysis
Command: npx skills add https://github.com/alohays/paper2pr --skill data-analysis-alohays

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the process of conducting complete data analysis workflows in R, enabling users to efficiently explore, model, and generate publication-ready outputs.

Core Features & Use Cases

End-to-end Analysis: Guides the user through data loading, exploration, model fitting, and result presentation.
Reproducibility: Ensures scripts follow coding conventions and produce consistent outputs.
Use Case: Imagine a researcher who obtains a CSV dataset and needs to run descriptive stats, fit regressions, and export formatted tables and figures for a paper.

Quick Start

Use the data-analysis skill to load your dataset and run a regression model with appropriate diagnostics and output formatting.

Frequently Asked Questions about data-analysis

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

FAQPage Schema

How do I streamline R data analysis workflows from data loading to publication?▼

R data analysis workflows are streamlined by guiding users through data loading, exploration, model fitting, and generating publication-ready tables and figures. This ensures reproducible scripts and well-documented results.

How do I generate publication-ready tables and figures for regression models in R?▼

Publication-ready tables and figures for regression models are generated by fitting the model and applying appropriate diagnostic checks. The workflow enforces coding standards to format and export consistent, documented outputs.

Can I use this workflow with a CSV dataset for descriptive stats and regression?▼

Yes, the workflow supports CSV datasets for running descriptive stats and fitting regressions. It is designed for researchers and analysts handling datasets who require reproducible, well-documented results.

What's the best way to ensure reproducibility in R data analysis scripts?▼

Reproducibility in R data analysis scripts is ensured by enforcing coding conventions and producing consistent outputs. The workflow includes diagnostic checks and requires scripts to follow specific coding standards.

Does the workflow include diagnostic checks for regression models?▼

Yes, diagnostic checks are included when fitting regression models. The workflow guides users through appropriate diagnostics and output formatting to ensure reliable, publication-ready results.