Design and execute statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python
Scanned 9/2/2026
Install to Claude Code
npx -y skills add a5c-ai/babysitter --skill quantitative-methods --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Quantitative Methods?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/a5c-ai-quantitative-methods-babysitter)More formats (shields.io, HTML) on the badges page.
---
name: quantitative-methods
description: Design and execute statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python
allowed-tools:
- Read
- Write
- Edit
- Grep
- Glob
- Bash
graph:
domains: [domain:social-sciences]
skillAreas: [skill-area:statistical-analysis, skill-area:data-analysis, skill-area:machine-learning-frameworks]
workflows: [workflow:experiment-design, workflow:peer-review-cycle]
roles: [role:data-scientist, role:research-scientist]
---
# Quantitative Methods Skill
Design and execute rigorous statistical analyses for social science research using modern analytical tools.
## Overview
The Quantitative Methods skill enables design and execution of statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python for rigorous quantitative social science research.
## Capabilities
### Regression Analysis
- Linear regression modeling
- Logistic and multinomial regression
- Panel data methods
- Time series analysis
- Hierarchical/multilevel modeling
### Hypothesis Testing
- Parametric tests
- Non-parametric alternatives
- Multiple comparison correction
- Effect size estimation
- Confidence interval construction
### Power Analysis
- Sample size determination
- Effect size specification
- Power calculation
- Design optimization
- Sensitivity analysis
### Robustness Checking
- Specification testing
- Outlier analysis
- Assumption verification
- Alternative estimators
- Sensitivity analysis
### Tool Proficiency
- R/RStudio workflows
- Stata programming
- SPSS procedures
- Python (statsmodels, scipy)
- Output visualization
## Usage Guidelines
### When to Use
- Designing quantitative studies
- Analyzing survey data
- Testing hypotheses
- Building predictive models
- Validating findings
### Best Practices
- Pre-register analyses
- Check assumptions
- Report fully
- Conduct robustness checks
- Document code
### Integration Points
- Causal Inference Methods skill
- Survey Design and Administration skill
- Psychometric Assessment skill
- Mixed Methods Integration skill
## References
- Statistical Analysis Pipeline process
- Experimental Design process
- Multilevel/Hierarchical Modeling process
- Quantitative Research Methodologist agent
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!