statsmodels
This skill provides direct access to Python's statsmodels library for statistical modeling. It covers OLS, logistic regression, ARIMA, GLM, and hypothesis testing with code examples. The documentation includes model selection guidance, formula API usage, and common applications like marketing response prediction.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install k-dense-ai-claude-scientific-skills-statsmodels
Repository
Skill path: scientific-skills/statsmodels
This skill provides direct access to Python's statsmodels library for statistical modeling. It covers OLS, logistic regression, ARIMA, GLM, and hypothesis testing with code examples. The documentation includes model selection guidance, formula API usage, and common applications like marketing response prediction.
Open repositoryBest for
Primary workflow: Grow & Distribute.
Technical facets: Data / AI, Backend, Testing.
Target audience: AI/ML teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: K-Dense-AI.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install statsmodels into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/K-Dense-AI/claude-scientific-skills before adding statsmodels to shared team environments
- Use statsmodels for ai/ml workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.